Design Support System

Abstract

A design support system is provided that is suitable for grasping a plurality of elements to be edited in succession and the order of editing. SOLUTION: A drawing creation support device 100 inputs a request including an already-created or edited element ID, and element order information relating to multiple edit elements to be edited in succession after the edit element and their edit order, to an AI model 50, the request including a generation request to generate multiple element order information with different edit elements or edit orders, obtains the multiple element order information output from the AI ​​model 50 in response to the request, and displays one of the multiple element orders based on the obtained multiple element order information. This makes it possible to grasp the multiple edit elements to be edited in succession and their edit order.

Description

[Technical field]

[0001] The present invention relates to a design support system, and more particularly to a design support system suitable for grasping a plurality of elements to be edited in succession and the order of editing them. [Background technology]

[0002] 2. Description of the Related Art Conventionally, as a technique for supporting design using AI (Artificial Intelligence), for example, the technique described in Patent Document 1 is known.

[0003] The technology described in Patent Document 1 assigns a reward R to a combination of a state S, which is determined depending on whether or not a design activity has been performed, and an action A, which is an activity that can be selected under the state, and builds a trained model by maximizing the value.The trained model is then used to infer the next action to be taken from the current state. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-56238 Summary of the Invention [Problem to be solved by the invention]

[0005] In architectural design, multiple related elements of a unit may be edited in succession. For example, when designing a toilet, the toilet bowl and hand washing basin are designed in succession. However, the technology described in Patent Document 1 has the problem that it is not possible to grasp multiple elements that are edited in succession and the order of editing, because the technology infers the next action to be taken from the current state.

[0006] Therefore, the present invention has been made in consideration of the unresolved problems of the conventional technology, and has an object to provide a design support system suitable for grasping multiple elements that are edited in succession and the order in which they are edited. [Means for solving the problem]

[0007] [Invention 1] In order to achieve the above object, the design support system of Invention 1 comprises: element information acquisition means for acquiring element information relating to created or edited elements in design information; input means for inputting a request including the element information acquired by the element information acquisition means and element order information relating to a plurality of elements to be edited consecutively after the element related to the element information and their editing order (hereinafter, "a plurality of elements and their editing order" will be referred to as "element order"), the request including a request to generate a plurality of said element order information having different elements or editing orders, to an AI model; acquisition means for acquiring the plurality of element order information output from the AI ​​model in response to the request; and output means for outputting one or a plurality of said element orders based on the plurality of element order information acquired by the acquisition means.

[0008] With this configuration, the element information acquisition means acquires element information, the input means inputs a request including the acquired element information and including a request to generate multiple pieces of element order information to the AI ​​model, the acquisition means acquires the multiple pieces of element order information to be output from the AI ​​model in response to the request, and the output means outputs one or multiple element orders based on the estimated multiple pieces of element order information.

[0009] Here, the input means includes, for example, directly inputting a request to the AI ​​model, or indirectly inputting the request to the AI ​​model via a process, function, device, network, or other means.

[0010] In addition, the acquisition means includes, for example, directly acquiring the output information of the AI ​​model, or indirectly acquiring the output information of the AI ​​model via processing, function, device, network, or other means.

[0011] Furthermore, the request to generate element order information includes, for example, a request to generate answer information to a question about element order.

[0012] Furthermore, the generation request includes, for example, an explicit request to generate element order information, and an indirect request to generate element order information. An explicit request includes, for example, a request such as "Please generate element order information." An indirect request includes, for example, a generation request that includes a question regarding element order in order to request the generation of answer information to the question regarding element order. This is because, in an AI model, if a question regarding element order is input as a prompt, the answer information is generated.

[0013] Furthermore, the element information and the request may be configured in any format, such as vector data.

[0014] Furthermore, the element information acquisition means may, for example, input element information from an input device or the like, acquire or receive element information from an external terminal or the like, read element information from a storage device or storage medium or the like, or generate or calculate element information by information processing or the like. Therefore, acquisition includes at least input, acquisition, reception, reading (including search), generation, and calculation. The same concept of acquisition applies hereinafter.

[0015] Furthermore, element information can be, for example, configured as the element itself, or as information for identifying the element (for example, name, number, ID, code, link information such as URL), or as feature information related to an outline, statistics, or other features of the element. Furthermore, element information can be, for example, configured as characters, numbers, figures, codes, symbols, images, sounds, and other information. Furthermore, element information can be configured as keywords related to the element (for example, one or more keywords indicating part of the name of the element).

[0016] Furthermore, the element order information can be configured, for example, as the element order itself, or as information for identifying the elements and the editing order (for example, link information such as a name, number, ID, code, or URL), or as feature information relating to an overview, statistics, or other features of the elements and the editing order. The element order information can be configured, for example, as characters, numbers, figures, codes, symbols, images, sounds, or other information. The element order information can be configured as keywords relating to the elements and the editing order (for example, one or more keywords indicating part of the name of the elements and the editing order).

[0017] The output means can output information by, for example, display, printing, audio output, writing to a storage device or storage medium, transmission to other equipment, devices, terminals, or other devices, vibration such as vibration, heat generation, or other methods. Therefore, output includes at least display, printing, audio output, writing, transmission, vibration, and heat generation. The same concept of output applies hereinafter.

[0018] The system may be realized as a single device, equipment, terminal, or other device, or as a network system in which multiple devices, equipment, terminals, or other devices are communicatively connected. In the latter case, each component may belong to any one of the multiple devices as long as they are communicatively connected to each other.

[0019] [Invention 2] Furthermore, the design support system of invention 2 is the design support system of invention 1, wherein the output means outputs an element sequence having the largest number of elements from among the plurality of element sequences.

[0020] With this configuration, the output means outputs the element sequence with the largest number of elements.

[0021] [Invention 3] The design support system of Invention 3 further comprises, in the design support system of Invention 1, an identification means for identifying, as a related group, the element sequences that appear a predetermined number of times in the design information, and the output means outputs, from the plurality of element sequences, an element sequence that has the related group identified by the identification means.

[0022] With this configuration, the identifying means identifies an element sequence that appears a predetermined number of times or more as a related group, and the output means outputs the element sequence having the identified related group.

[0023] [Invention 4] Furthermore, in the design support system of Invention 4, in the design support system of Invention 3, the output means outputs an element sequence that is the same as the related group identified by the identification means from among the multiple element sequences.

[0024] With this configuration, the output means outputs the same element order as the related group.

[0025] [Invention 5] The design support system of Invention 5 further comprises, in the design support system of Invention 1, an identification means for identifying, as a related group, the element sequence that appears a predetermined number of times in the design information, and the output means outputs a part of the related group identified by the identification means from among the multiple element sequences, an element sequence that includes the related group identified by the identification means and other elements.

[0026] With this configuration, the identification means identifies an element sequence that occurs a predetermined number of times or more as a related group, and the output means outputs a part of the related group from the element sequence that includes the identified related group and other elements.

[0027] [Invention 6] Furthermore, the design support system of Invention 6, in the design support system of any one of Inventions 1 to 5, further comprises: a second element information acquisition means for acquiring element information relating to an element created or edited based on the element order output by the output means; a second input means for inputting a request including the element information acquired by the second element information acquisition means, and element order information relating to a plurality of elements to be edited successively after the element related to the element information and their edit order, to the AI ​​model, the request including a request to generate a plurality of the element order information having different elements or edit orders; and a second acquisition means for acquiring the plurality of element order information output from the AI ​​model in response to the request.

[0028] With this configuration, element information is acquired by the second element information acquisition means, a request including the acquired element information and including a request to generate multiple pieces of element order information is input to the AI ​​model by the second input means, and the second acquisition means acquires the multiple pieces of element order information to be output from the AI ​​model in response to the request.

[0029] [Invention 7] Furthermore, the design support system of Invention 7, in the design support system of any one of Inventions 1 to 5, further comprises: second element information acquisition means for acquiring element information on an element created or edited based on the element order output by the output means; and estimation means for estimating, from the element information acquired by the second element information acquisition means, a trained model trained on the basis of training data including element information on an element that has already been created or edited, and element order information on a plurality of elements edited successively after the element, and their edit order, the element order information on a plurality of elements having different elements or edit orders.

[0030] With this configuration, the second element information acquisition means acquires element information, and the estimation means estimates a plurality of pieces of element order information from the acquired element information by using the trained model.

[0031] Here, the trained model may be one that has been trained based on training data that includes at least element information and element order information, and also includes one that has been trained based on training data that includes element information, element order information, and other information.

[0032] [Invention 8] Furthermore, the design support system of Invention 8, in the design support system of any one of Inventions 1 to 5, further comprises: second element information acquisition means for acquiring element information on an element created or edited based on the element order output by said output means; and search means for searching for a plurality of element order information of elements or a plurality of element order information having different edit orders corresponding to the element information acquired by the second element information acquisition means from a storage means for storing a plurality of elements to be edited successively after an already created or edited element and element order information on the plurality of elements to be edited and their edit order in association with the element information on the already created or edited elements.

[0033] With this configuration, the second element information acquisition means acquires element information, and the search means searches the storage means for a plurality of pieces of element order information corresponding to the acquired element information.

[0034] [Invention 9] Furthermore, the design support system of Invention 9, in the design support system of any one of Inventions 1 to 5, further comprises a second element information acquisition means for acquiring element information relating to elements created or edited based on the element order output by the output means, and an output rule change means for changing the output rule of the output means based on the element order output by the output means and the element information acquired by the second element information acquisition means.

[0035] With this configuration, the second element information acquisition means acquires the element information, and the output rule change means changes the output rule of the output means based on the output element sequence and the acquired element information.

[0036] [Invention 10] Furthermore, the design support system of Invention 10, in the design support system of Invention 1, further comprises a registration means for registering, in a knowledge base that can be referenced by the AI ​​model, reference information including element information on an element that has already been created or edited, and reference information including multiple elements to be edited consecutively after the element and element order information on the editing order, and the acquisition means acquires, in response to the request, the multiple element order information output from the AI ​​model by referring to the reference information in the knowledge base.

[0037] With this configuration, the registration means registers the reference information in the knowledge base. Then, the acquisition means acquires the plurality of pieces of element order information output from the AI ​​model in response to the request. At this time, the AI ​​model refers to the reference information in the knowledge base.

[0038] Here, the knowledge base stores reference information by any means and at any time, and may store reference information in advance, or may store reference information by external input or the like while the system is operating, without storing reference information in advance.

[0039] [Invention 11] Furthermore, in the design support system of Invention 11, in the design support system of Invention 10, the registration means registers in the knowledge base reference information including element information on an element that has already been created or edited, element order information on a plurality of elements to be edited successively after the element in question and the order in which they are edited, and evaluation values ​​related to the editing of the plurality of elements.

[0040] [Invention 12] Furthermore, the design support system of Invention 12 is the design support system of Invention 11, wherein the registration means registers, in the knowledge base, first reference information including the element information, the element order information, and the evaluation value based on a first index indicating an index of the value of the evaluation value, and second reference information including the element information, the element order information, and the evaluation value based on a second index different from the first index, and is provided with index information acquisition means for acquiring index information regarding the first index or the second index, and the input means inputs, to the AI ​​model, the request including a request to refer to either the first reference information or the second reference information of the knowledge base based on the index information acquired by the index information acquisition means.

[0041] With this configuration, the registration means registers the first reference information and the second reference information in the knowledge base. Then, the index information acquisition means acquires index information, and the input means inputs a request including a request to refer to either the first reference information or the second reference information in the knowledge base based on the acquired index information to the AI ​​model.

[0042] [Invention 13] Furthermore, in the design support system of Invention 13, in the design support system of Invention 1, the request includes reference information including element information on an element that has already been created or edited, and element order information on a plurality of elements to be edited successively after the element and the order in which they are edited.

[0043] With this configuration, the input means inputs a request including element information and reference information and including a request to generate multiple element order information to the AI ​​model, and the acquisition means acquires the multiple element order information output from the AI ​​model in response to the request.

[0044] [Invention 14] Furthermore, in the design support system of Invention 14, in the design support system of Invention 13, the request includes element information relating to an element that has already been created or edited, element order information relating to a plurality of elements to be edited successively after the element and the order in which they are edited, and reference information including evaluation values ​​relating to the editing of the plurality of elements.

[0045] [Invention 15] Furthermore, the design support system of Invention 15, in the design support system of Invention 14, further comprises an index information acquisition means for acquiring index information relating to a first index indicating an index of the value of the evaluation value or a second index different from the first index, and the input means inputs the request to the AI ​​model based on the index information acquired by the index information acquisition means, the request including either first reference information including the element information, the element order information, and the evaluation value based on the first index, or second reference information including the element information, the element order information, and the evaluation value based on the second index.

[0046] With this configuration, index information is acquired by the index information acquisition means, and a request including either the first reference information or the second reference information is input to the AI ​​model by the input means based on the acquired index information.

[0047] [Invention 16] Furthermore, the design support system of Invention 16 is the design support system of any one of Inventions 1 to 5, wherein the plurality of elements are elements that require human judgment for setting or changing, and the setting or change of the elements has an effect on other elements.

[0048] [Invention 17] Furthermore, the design support system of invention 17 is the design support system of any one of inventions 1 to 5, wherein the design information is design information for designing a building. Effect of the Invention

[0049] As described above, according to the design support system of invention 1, one or more element orders are output, so that it is possible to grasp a plurality of elements to be edited in succession and the order of editing thereof.

[0050] Furthermore, according to the design support system of the second aspect, since the element order with the largest number of elements is output, editing can be performed while imagining large editing units.

[0051] Furthermore, according to the design support system of the third or fifth aspect, an element sequence having related groups is output, so that editing can be performed while imagining the related groups.

[0052] Furthermore, according to the design support systems of Inventions 6 to 8, it is possible to obtain multiple pieces of element order information for the results of creation or editing based on the output element order, so that it is possible to grasp multiple elements that are edited consecutively and their editing order.

[0053] Furthermore, according to the design support system of the ninth aspect, the output rules can be changed according to the output result of the output means and the result of subsequent creation or editing.

[0054] Furthermore, according to the design support system of the invention 11 or 14, the order of elements with high evaluation values ​​can be grasped.

[0055] Furthermore, according to the design support system of Invention 12, it is possible to grasp the order of elements having high evaluation values ​​based on the first index or the second index.

[0056] Furthermore, according to the design support system of Invention 16, it is possible to grasp the element order taking into consideration the relationship between elements that require human judgment for their setting or change and other elements that are affected by the setting or change. [Brief description of the drawings]

[0057] [Figure 1] FIG. 1 is a diagram illustrating a hardware configuration of a drawing creation support device 100. [Diagram 2] FIG. 13 is a diagram showing the structure of CAD data for a plan view. [Diagram 3] FIG. 4 is a diagram showing a structure of edit history data. [Figure 4] 13 is a flowchart showing a learning data generation process. [Diagram 5] FIG. 2 is a diagram showing a structure of learning data. [Figure 6] 13 is a flowchart showing a trained model generation process. [Figure 7] FIG. 1 is a block diagram showing the process of generating and using a trained model. [Figure 8] 13 is a flowchart showing an element order information estimation process. [Figure 9] This is a plan showing the expected delivery of a piano. [Figure 10] FIG. 4 is a diagram showing a structure of edit history data. [Figure 11] FIG. 2 is a diagram showing a structure of learning data. [Figure 12] 13 is a flowchart showing an element order information estimation process. [Figure 13] 1 is a block diagram showing a configuration of a network system according to an embodiment of the present invention; [Figure 14] FIG. 1 is a functional block diagram of a generation AI server 120. [Figure 15] 13 is a flowchart showing a learning data registration process. [Figure 16] 13 is a flowchart showing an element order information acquisition process. [Figure 17] 13 is a flowchart showing an element order information acquisition process. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0058] First Embodiment A first embodiment of the present invention will be described below. Figures 1 to 9 are diagrams showing this embodiment.

[0059] [Configuration of this embodiment] First, the configuration of this embodiment will be described. FIG. 1 is a diagram showing a hardware configuration of a drawing production support device 100. As shown in FIG.

[0060] As shown in FIG. 1, the drawing creation support device 100 is composed of a CPU (Central Processing Unit) 30 which controls calculations and the entire system based on a control program, a ROM (Read Only Memory) 32 which stores the control program and the like for the CPU 30 in advance in a specified area, a RAM (Random Access Memory) 34 for storing data read from the ROM 32 etc. and calculation results required in the calculation process of the CPU 30, and an I / F (InterFace) 38 which mediates the input and output of data to and from external devices. These are connected to each other and capable of sending and receiving data by a bus 39 which is a signal line for transferring data.

[0061] Connected to the I / F 38 as external devices are an input device 40 consisting of a keyboard, mouse, etc. capable of inputting data as a human interface, a storage device 42 which stores data, tables, etc. as files, and a display device 44 which displays a screen based on an image signal.

[0062] CAD (Computer Aided Design) software and BIM (Building Information Modeling) software (hereinafter collectively referred to as "CAD software") are installed in the storage device 42. CAD software is software that assists in the creation of drawings in response to operations by a designer. When a request is made to start the CAD software, the CPU 30 starts a program for the CAD software stored in a specified area of ​​the ROM 32, and executes processing according to the program. The designer can start the CAD software to create plan drawings, detailed floor plans, and other architectural drawings.

[0063] Next, the data structure of the storage device 42 will be described. The storage device 42 stores CAD data of architectural drawings such as plan drawings, detailed floor plans, and the like.

[0064] FIG. 2 is a diagram showing the structure of CAD data of a plan view. As shown in Figure 2, CAD data for a rectangular plan is data constituting a detailed drawing of the cross section of a building, and is configured as data including one or more createable or editable elements (hereinafter referred to as "edit elements"). CAD data for a rectangular plan is created by a designer using CAD software. A designer creates a rectangular plan by creating, setting, changing or deleting (hereinafter referred to as "editing") edit elements in the CAD software. In the example of Figure 2, the edit elements of the floor, wall and ceiling of the area labeled "internal corridor" are arranged, and the edit elements of the floor, wall and ceiling of the area labeled "windbreak room" are arranged.

[0065] The same is true for CAD data of floor plan details and other architectural drawings, which are structured as data including one or more editing elements.

[0066] The storage device 42 stores, for each CAD data, editing history data indicating the history of editing of the editing elements. The CAD data reflects the final editing results related to the editing history data.

[0067] FIG. 3 is a diagram showing the structure of the edit history data. 3, the editing history data includes, for each edited element, element information 400 related to the edited element and editing time 402 required to edit the edited element in the order of editing. The element information 400 includes an element ID for identifying the edited element, an area that is the subject of editing of the edited element, and the edited element itself. The editing time 402 can be calculated, for example, by subtracting the editing start time from the editing end time.

[0068] In the example of Figure 3, the first related group shows that the edit elements of the toilet, "toilet bowl," "washing counter," "mirror," and "towel rack," were edited consecutively in that order. These edit elements were assigned element IDs "52," "53," "54," and "55," and the edit times were 35, 38, 70, and 94 minutes, respectively.

[0069] In addition, the second related group shows that the edit elements of the toilet, "exhaust fan," "lighting," "storage," and "outlet," are edited consecutively in that order. These edit elements are assigned element IDs "56," "57," "58," and "59," and the edit times were 94, 48, 42, and 74 minutes, respectively.

[0070] Also, as a third related group, the edit elements of the closet, "shelf," "hanging rail," "drawer," and "basket," are edited consecutively in that order. These edit elements are assigned element IDs "60," "61," "62," and "63," and the edit times were 96, 74, 84, and 22 minutes, respectively.

[0071] The fourth related group shows that the kitchen editing elements "floor material," "wall material," "counter," and "sink" were edited consecutively in that order. These editing elements were assigned element IDs "64," "65," "66," and "67," and took 42, 44, 35, and 32 minutes to edit, respectively.

[0072] The editing history data is used to create learning data, and therefore a large number of pieces of editing history data created in the past are stored in the storage device 42.

[0073] [Operation of this embodiment] Next, the operation of this embodiment will be described. [Learning data generation process] FIG. 4 is a flowchart showing the learning data generation process.

[0074] The learning data generation process is a process for generating learning data, and when executed by the CPU 30, the process proceeds to step S100 as shown in FIG.

[0075] In step S100, unprocessed editing history data is obtained from storage device 42, and the process proceeds to step S102, where variable n is set to "2", and the process proceeds to step S104.

[0076] In steps S104 to S108, the element ID of the edited element that has been created or edited (hereinafter abbreviated as "created or edited element ID"), the n edited elements (the number indicated by the value of variable n) that were edited consecutively after that edited element, their edit order, and their edit time are obtained from the edit history data obtained in step S100. Hereinafter, multiple edited elements and their edit order may be referred to as "element order." Using FIG. 3 as an example, a case where the value of variable n is "2" will be described. In the edit history data in FIG. 3, the rows are arranged in the edit order.

[0077] When the second row is targeted, the element IDs of the previous edited elements, "01" to "51", are obtained as the created or edited element IDs. Because the value of the variable n is "2", "toilet" and "washbasin counter" are obtained as the edited elements, and "35" and "38" are obtained as the edit times.

[0078] When the third row is targeted, the element IDs of the previous edited elements, "01" to "52", are obtained as the created or edited element IDs. Because the value of the variable n is "2", "hand washing counter" and "mirror" are obtained as the edited elements, and "38" and "70" are obtained as the edit times.

[0079] Next, the process proceeds to step S110, where the evaluation value is calculated by multiplying the sum of the editing times obtained in step S108 by "-1". In the example of the second line above, the editing times "35" and "38" are obtained, so the evaluation value is calculated as (35+38)×-1=-73. The reason for multiplying by "-1" is to set a higher evaluation value for shorter editing times.

[0080] Next, the process proceeds to step S112, where the element IDs and element orders obtained in steps S104 to S108 and the evaluation values ​​calculated in step S110 are associated with each other and registered in the learning data, the process proceeds to step S114, where "1" is added to the value of the variable n, and the process proceeds to step S116.

[0081] In step S116, it is determined whether the value of the variable n is greater than "4", and if it is determined that the value is less than or equal to "4" (NO), the process proceeds to step S104. Then, the processes of steps S104 to S114 are repeatedly executed until the value of the variable n becomes "4".

[0082] Using FIG. 3 as an example, the process of steps S104 to S110 will be described for the case where the value of the variable n is "3."

[0083] When the second row is targeted, the element IDs of the previous edited elements, "01" to "51", are obtained as the created or edited element IDs. Because the value of variable n is "3", the edited elements obtained are "toilet", "washing counter", and "mirror", and the edit times obtained are "35", "38", and "70". The evaluation value is calculated as (35 + 38 + 70) x -1 = -143.

[0084] When the third row is targeted, the element IDs of the previous edited elements, "01" to "52", are obtained as the created or edited element IDs. Because the value of the variable n is "3", the edited elements obtained are "hand washing counter", "mirror", and "towel rack", and the edit times obtained are "38", "70", and "94". The evaluation value is calculated as (38 + 70 + 94) x -1 = -202.

[0085] Moreover, the process of steps S104 to S110 will be described for the case where the value of the variable n is "4" using FIG. 3 as an example.

[0086] When the second row is targeted, the element IDs of the previous edited elements, "01" to "51", are obtained as the created or edited element IDs. Because the value of variable n is "4", the edited elements obtained are "toilet", "washing counter", "mirror", and "towel rack", and the edit times obtained are "35", "38", "70", and "94". The evaluation value is calculated as (35 + 38 + 70 + 94) x -1 = -237.

[0087] When the third row is targeted, the element IDs of the previous edited elements, "01" to "52", are obtained as the created or edited element IDs. Because the value of the variable n is "4", the edited elements obtained are "hand washing counter", "mirror", "towel rack", and "exhaust fan", and the edit times obtained are "38", "70", "94", and "94". The evaluation value is calculated as (38 + 70 + 94 + 94) x -1 = -296.

[0088] On the other hand, if it is determined in step S116 that the value of variable n is greater than "4" (YES), the process proceeds to step S118 to determine whether or not the processing of steps S100 to S116 has been completed for all of the editing history data, and if it is determined that the processing has been completed for all of the editing history data (YES), the process proceeds to step S120.

[0089] In step S120, the learning data in which the element IDs and other information have been registered in step S112 is stored in the storage device .

[0090] FIG. 5 is a diagram showing the structure of the learning data. 5, each line of the learning data includes a created or edited element ID 410, element order information 412, and an evaluation value 414. The element order information 412 includes an area to be edited by the edit element and an element order.

[0091] The second line of Fig. 5 shows two edit elements edited in succession after the edit element in the first line of Fig. 3, their edit order, and evaluation value, the third line of Fig. 5 shows two edit elements edited in succession after the edit element in the second line of Fig. 3, their edit order, and evaluation value, the fourth line of Fig. 5 shows two edit elements edited in succession after the edit element in the third line of Fig. 3, their edit order, and evaluation value, the sixth line of Fig. 5 shows two edit elements edited in succession after the edit element in the fifth line of Fig. 3, their edit order, and evaluation value, the seventh line of Fig. 5 shows two edit elements edited in succession after the edit element in the sixth line of Fig. 3, their edit order, and evaluation value, the eighth line of Fig. 5 shows two edit elements edited in succession after the edit element in the seventh line of Fig. 3, their edit order, and evaluation value,

[0092] Also, the 10th line of Fig. 5 shows three edit elements edited in succession after the edit element on the 1st line of Fig. 3, their edit order, and evaluation value, and the 11th line of Fig. 5 shows three edit elements edited in succession after the edit element on the 2nd line of Fig. 3, their edit order, and evaluation value, respectively. Also, the 13th line of Fig. 5 shows three edit elements edited in succession after the edit element on the 5th line of Fig. 3, their edit order, and evaluation value, and the 14th line of Fig. 5 shows three edit elements edited in succession after the edit element on the 6th line of Fig. 3, their edit order, and evaluation value, respectively.

[0093] In addition, line 16 of Figure 5 shows the four edit elements edited consecutively after the edit element on line 1 of Figure 3, their edit order, and evaluation value, and line 18 of Figure 5 shows the four edit elements edited consecutively after the edit element on line 5 of Figure 3, their edit order, and evaluation value.

[0094] [Trained model generation process] FIG. 6 is a flowchart showing the trained model generation process.

[0095] FIG. 7 is a block diagram showing the process of generating and using a trained model. The trained model generation process is a process executed to generate a trained model, and when executed by the CPU 30, the process proceeds to step S200 to execute a trained data analysis process, as shown in Fig. 6. In the trained data analysis process, the trained data is read from the storage device 42, and created or edited element IDs 410, element order information 412, and evaluation values ​​414 are extracted from the read trained data.

[0096] Next, the process proceeds to step S202. In step S202, as shown in FIG. 7, a learning data set is generated based on the information extracted in step S200, and the process proceeds to step S204, where the generated learning data set is input to a learning program, and a trained model is generated by the learning program. The learning program includes pre-learning parameters and hyperparameters, and performs learning based on the input learning data set and hyperparameters to update the pre-learning parameters. For example, reinforcement learning can be adopted as a learning method. In reinforcement learning, an evaluation value related to the editing of the multiple edit elements is given to a combination of an already created or edited element ID, a plurality of edit elements edited consecutively next to the edit element, and element order information related to the edit order, and learning is performed so that the evaluation value is maximized. Then, the trained model is output as a learning result.

[0097] The trained model is trained based on the created or edited element ID 410, element order information 412, and evaluation value 414 so that evaluation value 414 is maximized. The trained model includes trained parameters in which pre-trained parameters have been updated by training, and an inference program. The inference program inputs created or edited element IDs, estimates element order information from the input created or edited element IDs based on the trained parameters, and outputs the estimated element order information. Note that the relationship between the input element IDs and the output element order information is determined by AI training, and therefore, although it shows a similar tendency to the contents of past training data, there is ambiguity that does not necessarily match exactly. However, this ambiguity can be reduced by the amount of training data and the training accuracy.

[0098] Next, the process proceeds to step S206, where the trained model generated in step S204 is stored in the storage device 42, and the series of processes is terminated.

[0099] [Element order information estimation process] FIG. 8 is a flowchart showing the element order information estimation process.

[0100] The element order information inference process is executed in response to a request from a designer or other user, and when executed by CPU 30, first the process proceeds to step S300 as shown in FIG.

[0101] In step S300, an element ID that has been created or edited is obtained from the CAD data currently being edited, and the process proceeds to step S302.

[0102] In step S302, multiple pieces of element order information with different edit elements or edit orders are estimated from the element IDs acquired in step S300 using the trained model in the storage device 42. The estimation is performed by inputting created or edited element IDs to the trained model and acquiring element order information output from the trained model. For the trained model, multiple outputs may be acquired from one input, or multiple outputs may be acquired by repeating one input and one output multiple times.

[0103] Next, the process proceeds to step S304, where one of a plurality of element orders is displayed on the display device 44 according to one of a plurality of display rules based on the plurality of pieces of element order information estimated in step S302. Which display rule is to be used may be set, for example, by a designer or other user, or may be set according to a predetermined algorithm.

[0104] The first display rule is to display the element sequence with the largest number of edit elements among the multiple estimated element sequences.

[0105] The second display rule is to display an element order having a related group among the estimated element orders. For example, if the element orders estimated from the current edit state are (1) A, B, (2) A, B, C, (3) A, B, C, D, (4) A, B, C, D, E, and (5) A, B, C, D, E, F, and A to D are related groups among them, according to the second display rule, one of (3) to (5) is displayed. The determination of whether or not it is related groups can be performed by, for example, identifying two or more edit elements and their edit orders among A to F that have a predetermined number of occurrences or more in the learning data. The same applies to the third and fourth display rules.

[0106] The third display rule is to display the same element order as a group of related elements among the estimated element orders. For example, if the element orders estimated from the current editing state are (1) to (5) above, the third display rule displays (3).

[0107] The fourth display rule is to display related groups among the estimated element sequences and related groups from element sequences including other edited elements. For example, if the element sequences estimated from the current edit state are (1), (2), and (5) above, according to the fourth display rule, A to D are displayed from (5).

[0108] Next, proceed to step S306, where if the designer creates or edits an edit element based on the displayed element order, the created or edited element ID including the element ID of the edit element is obtained from the CAD data currently being edited, and proceed to step S308.

[0109] In step S308, based on the element order displayed in steps S304 and S314 and the element IDs acquired in step S306, it is determined whether the edited elements created or edited by the designer differ from the edited elements or edit order displayed in steps S304 and S314. If it is determined that the edited result differs from the estimated result (YES), the process proceeds to step S310.

[0110] In step S310, the display rules used for display in steps S304 and S314 are changed. For example, the display rules are changed to optimal ones so that the edited result matches the estimated result. The timing of changing the display rules does not have to be every time one creation or edit is made, and may be every time multiple creations or edits are made.

[0111] Next, the process proceeds to step S312, where similarly to the process of step S302, multiple pieces of element order information are estimated from the element IDs acquired in step S306 using the trained model in the storage device 42, and the process proceeds to step S314.

[0112] In step S314, similarly to the process in step S304, one of the plurality of element orders is displayed on display device 44 based on the plurality of pieces of element order information estimated in step S312, and the process proceeds to step S316.

[0113] In step S316, it is determined whether or not the editing by the designer has been completed, and if it is determined that the editing has been completed (YES), the series of processes is terminated.

[0114] On the other hand, if it is determined in step S316 that the editing by the designer has not been completed (NO), the process proceeds to step S306.

[0115] On the other hand, if it is determined in step S308 that the edited result matches the estimated result (NO), the process proceeds to step S312.

[0116] [When considering bringing in a piano] Next, an operation will be described assuming that a piano is brought in.

[0117] FIG. 9 is a plan illustrating the delivery of a piano. When a designer wants to install a piano with a width of 120 mm in the plan view of FIG. 9 in the CAD software, the width of the toilet needs to be shortened to prevent interference between the piano and the toilet wall when the piano is brought in. However, when the width of the toilet is changed, other edit elements of the toilet also need to be edited. Therefore, when the designer requests estimation of the element order to be edited for the toilet after changing the width of the toilet, the element IDs that have already been created or edited are acquired from the CAD data currently being edited through steps S300 to S304, and the element order is estimated and displayed from the acquired element IDs. For example, when the element order information of the 16th line in FIG. 5 is estimated, "toilet bowl → hand washing counter → mirror → towel rack" is displayed. As shown in FIG. 9, if these edit elements are already included in the CAD data, for example, these edit elements are highlighted (for example, displayed with a specific color or pattern) and the edit order is displayed by connecting them with arrows or the like. If they are not included in the CAD data, for example, these edit elements are ghost displayed (for example, a ghost image of the edit element is displayed in a wireframe) and the edit order is displayed by connecting them with arrows or the like.

[0118] Then, when the designer creates or edits the edit element "toilet" based on the estimated and displayed element order, the next element order is estimated and displayed through steps S306 to S314. If the designer's editing result differs from the estimated result, the display rules are changed through step S310.

[0119] [Effects of this embodiment] Next, the effects of this embodiment will be described. In this embodiment, a created or edited element ID is obtained, and multiple pieces of element order information are estimated from the obtained element ID using a trained model, and one of multiple element orders is displayed based on the estimated multiple pieces of element order information.

[0120] This makes it possible to grasp a plurality of edit elements that are edited successively and the order of editing them.

[0121] Furthermore, in this embodiment, the element order with the largest number of edit elements out of the multiple estimated element orders is displayed.

[0122] This allows the designer to carry out editing while imagining larger editing units. Furthermore, in this embodiment, element orders that appear a predetermined number of times or more in the training data are identified as related groups, and element orders having related groups from among the multiple estimated element orders are displayed.

[0123] This allows the designer to carry out editing while visualizing related groups.

[0124] Furthermore, in this embodiment, an element sequence that appears a predetermined number of times or more in the training data is identified as a related group, and an element sequence that is the same as the related group among the multiple estimated element sequences is displayed.

[0125] This allows the designer to carry out editing while visualizing related groups.

[0126] Furthermore, in this embodiment, element sequences that appear a predetermined number of times or more in the training data are identified as related groups, and from among the multiple estimated element sequences, the related groups and the element sequences that include other edited elements, parts that have related groups are displayed.

[0127] This allows the designer to carry out editing while visualizing related groups.

[0128] Furthermore, in this embodiment, created or edited element IDs including the element IDs of edited elements created or edited by the designer are obtained based on the displayed element order, and multiple pieces of element order information are estimated from the obtained element IDs using the trained model, and one of multiple element orders is displayed based on the multiple pieces of estimated element order information.

[0129] As a result, the element order is estimated and displayed for the result of creation or editing based on the displayed element order, so that a plurality of edit elements that are edited consecutively and their edit order can be grasped.

[0130] Furthermore, in this embodiment, created or edited element IDs, including the element IDs of edited elements created or edited by the designer, are obtained based on the displayed element order, and the display rules are changed based on the displayed element order and the obtained element IDs.

[0131] This allows the display rules to be changed depending on the display result of the element order and the result of subsequent creation or editing.

[0132] Furthermore, in this embodiment, the trained model is trained to maximize the evaluation value based on learning data including a created or edited element ID, multiple edit elements edited consecutively after that edit element and element order information relating to the edit order, and evaluation values ​​relating to the editing of the multiple edit elements.

[0133] This makes it possible to grasp the order of elements with high evaluation values. Furthermore, in this embodiment, an evaluation value related to the editing of the multiple edited elements is assigned to a combination of an already created or edited element ID, multiple edited elements edited consecutively after the edited element, and element order information related to the editing order, and a trained model is generated by performing training so as to maximize the evaluation value.

[0134] This makes it possible to obtain a trained model that provides an element order with a high evaluation value. Second Embodiment Next, a second embodiment of the present invention will be described. Figures 10 to 12 are diagrams showing this embodiment. Figures 3, 5 and 9 are also used.

[0135] This embodiment differs from the first embodiment in that estimation is performed using a first trained model and a second trained model that have been trained using evaluation values ​​based on different indices. Hereinafter, only the parts that differ from the first embodiment will be described, and a description of the overlapping parts will be omitted.

[0136] [Configuration of this embodiment] First, the configuration of this embodiment will be described. FIG. 10 is a diagram showing the structure of the edit history data.

[0137] The storage device 42 stores the edit history data of FIG. 10 in addition to the edit history data of FIG. 3 for each CAD data.

[0138] As shown in FIG. 10, the edit history data includes, for each edit element, element information 404 relating to the edit element and the number of edit items 406 required to edit the edit element, in the order of editing.

[0139] In the example of Figure 10, the first related group shows that the edit elements of the toilet, "toilet bowl," "washing counter," "mirror," and "towel rack," are edited consecutively in that order. These edit elements are assigned element IDs "52," "53," "54," and "55," and the number of edit items is 8, 5, 6, and 9, respectively.

[0140] Also, as a second related group, the edit elements of the toilet, "exhaust fan," "lighting," "storage," and "outlet," are edited consecutively in that order. These edit elements are assigned element IDs "56," "57," "58," and "59," and the number of edit items is 3, 7, 8, and 6, respectively.

[0141] Also, as a third related group, the edit elements of the closet, "shelf," "hanging rail," "drawer," and "basket," are shown to have been edited consecutively in that order. These edit elements are assigned element IDs "60," "61," "62," and "63," and the number of edit items is 8, 7, 2, and 4, respectively.

[0142] Also, as the fourth related group, the kitchen edit elements "floor material," "wall material," "counter," and "sink" are edited consecutively in that order. These edit elements are assigned element IDs "64," "65," "66," and "67," and the number of edit items is 7, 4, 3, and 8, respectively.

[0143] [Operation of this embodiment] Next, the operation of this embodiment will be described. [Learning data generation process] In the learning data generation process, similarly to the generation of the learning data in FIG. 5, learning data is generated based on the editing history data in FIG.

[0144] FIG. 11 is a diagram showing the structure of the learning data. As shown in FIG. 11, the learning data includes created or edited element IDs 410, element order information 412, and evaluation values ​​414 for each line.

[0145] The second line of Fig. 11 shows two edit elements edited in succession after the edit element in the first line of Fig. 10, their edit order, and evaluation value, the third line of Fig. 11 shows two edit elements edited in succession after the edit element in the second line of Fig. 10, their edit order, and evaluation value, the fourth line of Fig. 11 shows two edit elements edited in succession after the edit element in the third line of Fig. 10, their edit order, and evaluation value, the sixth line of Fig. 11 shows two edit elements edited in succession after the edit element in the fifth line of Fig. 10, their edit order, and evaluation value, the seventh line of Fig. 11 shows two edit elements edited in succession after the edit element in the sixth line of Fig. 10, their edit order, and evaluation value, the eighth line of Fig. 11 shows two edit elements edited in succession after the edit element in the seventh line of Fig. 10, their edit order, and evaluation value, respectively.

[0146] 11 shows three edit elements edited in succession after the edit element on the first line of Fig. 10, their edit order, and evaluation value, while the 11th line of Fig. 11 shows three edit elements edited in succession after the edit element on the second line of Fig. 10, their edit order, and evaluation value, while the 13th line of Fig. 11 shows three edit elements edited in succession after the edit element on the fifth line of Fig. 10, their edit order, and evaluation value, while the 14th line of Fig. 11 shows three edit elements edited in succession after the edit element on the sixth line of Fig. 10, their edit order, and evaluation value, respectively.

[0147] In addition, line 16 of Figure 11 shows the four edit elements that are edited consecutively after the edit element on line 1 of Figure 10, their edit order, and their evaluation value, and line 18 of Figure 11 shows the four edit elements that are edited consecutively after the edit element on line 5 of Figure 10, their edit order, and their evaluation value.

[0148] [Trained model generation process] In the trained model generation process, through steps S200 to S204, a first trained model is generated by performing learning based on the learning data in Fig. 5. The first trained model is similar to the trained model in the above-described first embodiment.

[0149] In the trained model generation process, after steps S200 to S204, a second trained model is generated by performing learning based on the learning data in Fig. 11, similar to the generation of the first trained model. The second trained model is trained so as to maximize the evaluation value 420 based on the created or edited element IDs 416, element order information 418, and evaluation value 420.

[0150] Then, the process proceeds to step S206, where the first trained model and the second trained model generated in step S204 are stored in the storage device 42, and the series of processes is terminated.

[0151] [Element order information estimation process] FIG. 12 is a flowchart showing the element order information estimation process.

[0152] The element order information inference process is executed in response to a request from a designer or other user, and when executed by CPU 30, first the process proceeds to step S350 as shown in FIG.

[0153] In step S350, index information regarding the first index "editing time" or the second index "number of edited items" indicating an index of the value of the evaluation value is obtained, and the process proceeds to step S352, where if the index related to the obtained index information is the first index, the first trained model is selected, and if the index related to the obtained index information is the second index, the second trained model is selected.

[0154] Next, the process proceeds to step S354, where the created or edited element ID is obtained from the CAD data currently being edited, and the process proceeds to step S356.

[0155] In step S356, a plurality of pieces of element order information are estimated from the element IDs acquired in step S354 using the trained model selected in step S352 from the first trained model and the second trained model in the storage device 42 (hereinafter referred to as the "selected trained model"). The estimation method is the same as the process in step S302 in the first embodiment.

[0156] Next, the process proceeds to step S358, where, similar to the process of step S304, one of the plurality of element orders is displayed on display device 44 based on the plurality of element order information estimated in step S356, and the process proceeds to step S360.

[0157] In step S360, if the designer creates or edits an edit element based on the displayed element order, the created or edited element ID including the element ID of the edit element is obtained from the CAD data currently being edited, and the process proceeds to step S362.

[0158] In step S362, based on the element order displayed in steps S358 and S368 and the element IDs acquired in step S360, it is determined whether the edited elements created or edited by the designer differ from the edited elements or edit order displayed in steps S358 and S368, and if it is determined that the edited result differs from the estimated result (YES), the process proceeds to step S364.

[0159] In step S364, similarly to the process in step S310, the display rules used in the displays in steps S358 and S368 are changed, and the process proceeds to step S366.

[0160] In step S366, similar to the processing in step S356, multiple pieces of element order information are estimated from the element IDs acquired in step S360 using the selected trained model, and the process proceeds to step S368.

[0161] In step S368, similar to the process in step S358, one of the plurality of element orders is displayed on display device 44 based on the plurality of pieces of element order information estimated in step S312, and the process proceeds to step S370.

[0162] In step S370, it is determined whether or not editing by the designer has ended, and if it is determined that editing has ended (YES), the series of processes ends.

[0163] On the other hand, if it is determined in step S370 that the editing by the designer has not been completed (NO), the process proceeds to step S360.

[0164] On the other hand, if it is determined in step S362 that the edited result matches the estimated result (NO), the process proceeds to step S366.

[0165] [When considering bringing in a piano] Next, an operation will be described assuming that a piano is brought in.

[0166] When a designer wants to install a piano with a width of 120 mm in the plan view of FIG. 9 in the CAD software, the width of the toilet needs to be shortened to prevent interference between the piano and the toilet wall when the piano is brought in. However, if the width of the toilet is changed, other editing elements of the toilet also need to be edited. Therefore, the designer requests an estimation of the element order to be edited for the toilet after changing the width of the toilet. At this time, if an element order that shortens the editing time is desired, the designer selects "editing time" as an index, and the first trained model is selected through steps S350 to S352. Then, through steps S354 to S358, the created or edited element IDs are acquired from the CAD data currently being edited, and the element order is estimated and displayed from the acquired element IDs by the first trained model.

[0167] On the other hand, if an element order that reduces the number of edited items is desired, the designer selects "number of edited items" as the index, and the second trained model is selected through steps S350 to S352. Then, through steps S354 to S358, created or edited element IDs are acquired from the CAD data currently being edited, and the element order is estimated and displayed from the acquired element IDs by the second trained model.

[0168] [Effects of this embodiment] Next, the effects of this embodiment will be described. In this embodiment, index information regarding the first index or the second index is acquired, either the first trained model or the second trained model is selected based on the acquired index information, created or edited element IDs are acquired, and multiple element order information is estimated from the acquired element IDs using the selected trained model.

[0169] This makes it possible to ascertain the order of elements with high evaluation values ​​based on the first index or the second index.

[0170] Third embodiment Next, a third embodiment of the present invention will be described. Figures 13 to 16 are diagrams showing this embodiment. Figures 3, 5 and 9 are also used.

[0171] This embodiment differs from the first embodiment in that a large language model is used. Hereinafter, only the differences from the first embodiment will be described, and the description of the overlapping parts will be omitted.

[0172] [Configuration of this embodiment] First, the configuration of this embodiment will be described. FIG. 13 is a block diagram showing a configuration of a network system according to this embodiment.

[0173] As shown in FIG. 13, the drawing creation support device 100 and a generation AI server 120 that generates answer information by an AI (Artificial Intelligence) model in response to a request are connected to the Internet 199 so as to be able to communicate with each other.

[0174] [Generation AI Server 120] Next, the configuration of the generation AI server 120 will be described. Like the drawing creation support device 100, the generation AI server 120 has a hardware configuration similar to that of a general computer in which a CPU, ROM, RAM, I / F, etc. are connected via a bus, and is configured as, for example, a cloud server.

[0175] FIG. 14 is a functional block diagram of the generation AI server 120. As shown in FIG. 14, the generation AI server 120 is configured to include a plurality of AI models 50, an AI model control unit 52 that controls the AI ​​models 50, and a knowledge base 54 that registers data that the AI ​​models 50 refer to for inference.

[0176] The AI ​​model 50 is an AI model trained on a large data set, and is a highly versatile model capable of performing various tasks. For example, a large-scale language model can be adopted as the AI ​​model 50. The large-scale language model is a deep learning model that pre-learns from a huge amount of data what is called a language model that models human spoken words based on their occurrence probability. When a prompt is input, the large-scale language model statistically infers the generation probability of the next word from the sentence included in the input prompt, and outputs the inference result. For example, the publicly known technology described in the Internet sites "https: / / chatgpt-lab.com / n / n418d3aa56f0b" and "https: / / agirobots.com / chatgpt-mechanism-and-problem / " can be adopted as the large-scale language model. More specifically, for example, Titan Text G1 - Express, Titan Text G1 - Lite, Titan Image Generator G1, Titan Embeddings G1 - Text, Titan Embeddings Text V2, Titan Multimodal Embeddings G1, Claude, Claude Instant, Claude 3 Sonnet, Claude 3 Haiku, Claude 3 Opus, Jurassic-2 Mid, Jurassic-2 Ultra, Command, Command Light, Command R, Command R+, Embed English, Embed Multilingual, Llama 2 Chat 13B, Llama 2 Chat 70B, Llama 2 13B, Llama 2 70B, Llama 3 8b Instruct, Llama 3 70b Instruct, Mistral 7B Instruct, Mixtral 8X7B Instruct, Mistral Large, and Stable Diffusion XL can be adopted.

[0177] The AI ​​model control unit 52 selects one to be used for inference from among multiple AI models 50 in response to a selection request from the request processing unit 58. Furthermore, when a reference request is input from the request processing unit 58, it causes the selected AI model 50 (hereinafter referred to as the "selected AI model") to refer to the data in the knowledge base 54 in response to the input reference request. Furthermore, when a prompt is input from the request processing unit 58, it inputs the input prompt to the selected AI model. Then, when an execution request is input from the request processing unit 58, it causes the selected AI model to execute inference in response to the input execution request, obtains an inference result from the selected AI model, and outputs the obtained inference result to the request processing unit 58.

[0178] Learning data can be registered in the knowledge base 54. Information registered in the knowledge base 54 is in a data format (for example, vector data) that can be referenced by the AI ​​model 50.

[0179] The generation AI server 120 is further configured to have a request receiving unit 56 that receives requests, a request processing unit 58 that processes the requests received by the request receiving unit 56, and an answer information sending unit 60 that sends answer information to the request received by the request receiving unit 56 to the drawing creation support device 100.

[0180] The request receiving unit 56 receives a request for generating answer information from the drawing creation support device 100, and outputs the received request to the request processing unit 58. The request includes (1) an element ID that has already been created or edited, (2) a generation request for generating multiple edit elements to be edited consecutively after the edit element that has already been created or edited, and element order information regarding the edit order, (3) a selection request for selecting the AI ​​model 50, and (4) a reference request for referencing the learning data in the knowledge base 54. (3) and (4) are not essential but are included additionally.

[0181] When the request received by the request receiving unit 56 includes a selection request or a reference request, the request processing unit 58 outputs the selection request or the reference request to the AI ​​model control unit 52. In addition, based on the request received by the request receiving unit 56, the request processing unit 58 generates a prompt that instructs the AI ​​model 50. For example, the prompt is a request to the AI ​​model 50 to generate, based on the created or edited element ID, a plurality of edit elements to be edited next to the created or edited edit element and element order information regarding the edit order, which has an evaluation value of a predetermined value or more. Then, the generated prompt and execution request are output to the AI ​​model control unit 52, and when an inference result is input from the AI ​​model control unit 52 in response to the execution request, the inference result is output to the answer information sending unit 60.

[0182] The answer information sending unit 60 sends answer information including the inference result input from the request processing unit 58 to the drawing creation support apparatus 100 .

[0183] The generation AI server 120 further includes a request receiving unit 62 that receives requests, and a learning data registration unit 64 that registers the learning data in the knowledge base 54.

[0184] The request receiving unit 62 receives a request for registering learning data from the drawing production support device 100, and outputs the received request to the learning data registration unit 64. The request includes (1) learning data.

[0185] The learning data registration unit 64 stores the learning data included in the request received by the request receiving unit 62 in a storage (not shown) and converts it into a data format (e.g., vector data) that can be referenced by the AI ​​model 50. The vector data can be generated by a technique (embedding) for converting data including characters, images, sounds, etc. into a numerical vector. Then, the converted learning data is registered in the knowledge base 54. In response to a reference request from the request processing unit 58, the AI ​​model control unit 52 causes the selected AI model to refer to the learning data.

[0186] [Operation of this embodiment] Next, the operation of this embodiment will be described. [Learning data registration process] FIG. 15 is a flowchart showing the learning data registration process.

[0187] The learning data registration process is executed in response to a request from a designer or other user, and when executed by CPU 30, first, the process proceeds to step S400 as shown in FIG.

[0188] In step S400, the learning data in FIG. 5 is obtained from the storage device 42, and the process proceeds to step S402.

[0189] In step S402, a request for registering the learning data is sent to the generation AI server 120. The request includes (1) the learning data acquired in step S400.

[0190] When the process of step S402 ends, the series of processes ends. [Element order information acquisition process] FIG. 16 is a flowchart showing the element order information acquisition process.

[0191] The element order information acquisition process is executed in response to a request from a designer or other user, and when executed by CPU 30, first the process proceeds to step S500 as shown in FIG.

[0192] In step S500, an element ID that has been created or edited is obtained from the CAD data currently being edited, and the process proceeds to step S502.

[0193] In step S502, a request for generating answer information based on the element ID acquired in step S500 is sent to the generation AI server 120. The request includes (1) the element ID acquired in step S500, (2) a generation request for generating a plurality of element order information related to a plurality of edit elements to be edited consecutively after an edit element that has already been created or edited and the order of the edit elements, the plurality of element order information having different edit elements or edit orders, (3) a selection request for selecting a predetermined AI model 50, and (4) a reference request for referencing the learning data in the knowledge base 54.

[0194] Next, the process proceeds to step S504, where answer information is received from the generation AI server 120, and the process proceeds to step S506, where, similar to the processing of step S304, one of the multiple element orders is displayed on the display device 44 based on the multiple element order information contained in the received answer information, and the process proceeds to step S508.

[0195] In step S508, if the designer creates or edits an edit element based on the displayed element order, the created or edited element ID including the element ID of the edit element is obtained from the CAD data currently being edited, and the process proceeds to step S510.

[0196] In step S510, based on the element order displayed in steps S506 and S518 and the element IDs acquired in step S508, it is determined whether the edited elements created or edited by the designer differ from the edited elements or edit order displayed in steps S506 and S518. If it is determined that the edited result differs from the inference result (YES), the process proceeds to step S512.

[0197] In step S512, similarly to the process in step S310, the display rules used in the displays in steps S506 and S518 are changed, and the process proceeds to step S514.

[0198] In step S514, similar to the process in step S502, a request for generating answer information based on the element ID acquired in step S508 is sent to the generation AI server 120, and the process proceeds to step S516.

[0199] In step S516, similar to the processing in step S504, answer information is received from the generation AI server 120, and the process proceeds to step S518, where, similar to the processing in step S304, one of multiple element orders is displayed on the display device 44 based on the multiple element order information contained in the received answer information, and the process proceeds to step S520.

[0200] In step S520, it is determined whether or not the editing by the designer has ended, and if it is determined that the editing has ended (YES), the series of processes is ended.

[0201] On the other hand, if it is determined in step S520 that the editing by the designer has not been completed (NO), the process proceeds to step S508.

[0202] On the other hand, if it is determined in step S510 that the editing result matches the inference result (NO), the process proceeds to step S514.

[0203] [When considering bringing in a piano] Next, an operation will be described assuming that a piano is brought in.

[0204] When a designer wants to install a piano with a width of 120 [mm] in the plan of FIG. 9 in the CAD software, the width of the toilet needs to be shortened to prevent interference between the piano and the toilet wall when the piano is brought in. However, if the width of the toilet is changed, other editing elements of the toilet also need to be edited. Therefore, when the designer requests inference of the element order to be edited for the toilet after changing the width of the toilet, the created or edited element ID is acquired from the CAD data currently being edited through steps S500 to S506, and the element order is inferred and displayed from the acquired element ID. In the inference, the learning data of the knowledge base 54 is referenced by the selection AI model. The method of displaying the element order is the same as that of the first embodiment.

[0205] Then, when the designer creates or edits the edit element "toilet" based on the inferred and displayed element order, the next element order is inferred and displayed through steps S508 to S518. If the designer's editing result differs from the inferred result, the display rules are changed through step S512.

[0206] [Effects of this embodiment] Next, the effects of this embodiment will be described. In this embodiment, a request including a created or edited element ID, and element order information relating to multiple edit elements to be edited consecutively after the edit element and their edit order, is input to AI model 50, and includes a generation request to generate multiple element order information with different edit elements or edit orders.In response to the request, the multiple element order information output from AI model 50 is obtained, and one of the multiple element orders is displayed based on the obtained multiple element order information.

[0207] This makes it possible to grasp a plurality of edit elements that are edited successively and the order in which they are edited.

[0208] Furthermore, in this embodiment, learning data including an already created or edited element ID, multiple edit elements edited consecutively after that edit element and element order information regarding the edit order, and evaluation values ​​regarding the editing of the multiple edit elements is registered in the knowledge base 54, and in response to a request, the learning data in the knowledge base 54 is referenced to obtain multiple pieces of element order information output from the AI ​​model 50.

[0209] This makes it possible to grasp the order of elements with high evaluation values. Furthermore, in this embodiment, a created or edited element ID including the element ID of the edit element created or edited by the designer is obtained based on the displayed element order, and a request including a generation request to generate multiple element order information regarding multiple edit elements that are to be edited consecutively after the edit element and their edit order, which includes the obtained element ID, and which has different edit elements or edit orders, is input to the AI ​​model 50, and in response to the request, multiple element order information output from the AI ​​model 50 is obtained, and one of the multiple element orders is displayed based on the obtained multiple element order information.

[0210] As a result, the element order is inferred and displayed for the result of creation or editing based on the displayed element order, so that a plurality of edit elements that are edited consecutively and their edit order can be grasped.

[0211] In this embodiment, step S402 corresponds to the registration means of invention 10 or 11, step S500 corresponds to the element information acquisition means of invention 1, step S502 corresponds to the input means of invention 1, and step S504 corresponds to the acquisition means of invention 1 or 10. Also, steps S506 and S518 correspond to the output means of inventions 1 to 6 or 9, or the identification means of inventions 3 to 5, step S508 corresponds to the second element information acquisition means of invention 6 or 9, and steps S510 and S512 correspond to the output rule change means of invention 9.

[0212] In this embodiment, step S514 corresponds to the second input means of invention 6, step S516 corresponds to the second acquisition means of invention 6, the CAD data corresponds to the design information of invention 3, 5 or 17, and the created or edited element ID corresponds to the element information of invention 1, 6, 9 to 11. Moreover, the learning data corresponds to the reference information of invention 10 or 11.

[0213] [Fourth embodiment] Next, a fourth embodiment of the present invention will be described. Fig. 17 is a diagram showing this embodiment. Figs. 5, 9, 11, and 15 are also used.

[0214] This embodiment differs from the second and third embodiments in that the AI ​​model 50 refers to first learning data including an evaluation value based on a first index or second learning data including an evaluation value based on a second index. Hereinafter, only the parts that differ from the second and third embodiments will be described, and a description of the overlapping parts will be omitted.

[0215] [Operation of this embodiment] Next, the operation of this embodiment will be described. [Learning data registration process] The learning data registration process is executed in response to a request from a designer or other user, and when executed by CPU 30, first, the process proceeds to step S400 as shown in FIG.

[0216] In step S400, the learning data in FIG. 5 and the learning data in FIG. 11 are obtained from the storage device 42, and the process proceeds to step S402.

[0217] In step S402, a request for registering the learning data is sent to the generation AI server 120. The request includes (1) the learning data of Fig. 5 acquired in step S400 as the first learning data, and (2) the learning data of Fig. 11 acquired in step S400 as the second learning data.

[0218] When the process of step S402 ends, the series of processes ends. [Element order information acquisition process] FIG. 17 is a flowchart showing the element order information acquisition process.

[0219] The element order information acquisition process is executed in response to a request from a designer or other user, and when executed by CPU 30, first the process proceeds to step S550 as shown in FIG.

[0220] In step S550, index information regarding the first index "editing time" or the second index "number of edited items", which indicate indicators of the value of the evaluation value, is obtained, and then the process proceeds to step S552 to obtain the created or edited element ID from the CAD data currently being edited, and the process proceeds to step S554.

[0221] In step S554, a request for generating answer information is sent to the generation AI server 120 based on the index information acquired in step S550 and the element ID acquired in step S552. The request includes (1) the element ID acquired in step S552, (2) a generation request for generating a plurality of element order information related to a plurality of edit elements to be edited consecutively after an edit element that has already been created or edited and the order of the edit elements, the plurality of element order information having different edit elements or edit orders, (3) a selection request for selecting a predetermined AI model 50, and (4) a reference request for referencing the first learning data in the knowledge base 54 if the index related to the index information acquired in step S550 is the first index, or a reference request for referencing the second learning data in the knowledge base 54 if the index related to the index information acquired in step S550 is the second index.

[0222] Next, the process proceeds to step S556, where answer information is received from the generation AI server 120, and the process proceeds to step S558, where, similar to the processing of step S304, one of multiple element orders is displayed on the display device 44 based on the multiple element order information contained in the received answer information, and the process proceeds to step S560.

[0223] In step S560, if the designer creates or edits an edit element based on the displayed element order, the created or edited element ID including the element ID of the edit element is obtained from the CAD data currently being edited, and the process proceeds to step S562.

[0224] In step S562, based on the element order displayed in steps S558 and S570 and the element IDs acquired in step S508, it is determined whether the edited elements created or edited by the designer differ from the edited elements or edit order displayed in steps S558 and S570. If it is determined that the edited result differs from the inference result (YES), the process proceeds to step S564.

[0225] In step S564, similarly to the process in step S310, the display rules used for display in steps S558 and S570 are changed, and the process proceeds to step S566.

[0226] In step S566, similar to the processing in step S554, a request for generating answer information based on the index information acquired in step S550 and the element ID acquired in step S560 is sent to the generation AI server 120, and the process proceeds to step S568.

[0227] In step S568, as in the processing of step S556, answer information is received from the generation AI server 120, and the process proceeds to step S570, where, as in the processing of step S304, one of multiple element orders is displayed on the display device 44 based on the multiple element order information contained in the received answer information, and the process proceeds to step S572.

[0228] In step S572, it is determined whether or not editing by the designer has ended, and if it is determined that editing has ended (YES), the series of processes is terminated.

[0229] On the other hand, if it is determined in step S572 that the editing by the designer has not been completed (NO), the process proceeds to step S560.

[0230] On the other hand, if it is determined in step S562 that the editing result matches the inference result (NO), the process proceeds to step S566.

[0231] [When considering bringing in a piano] Next, an operation will be described assuming that a piano is brought in.

[0232] When a designer wants to install a piano with a width of 120 mm in the plan of FIG. 9 in the CAD software, the width of the toilet needs to be shortened to prevent interference between the piano and the toilet wall when the piano is brought in. However, if the width of the toilet is changed, other editing elements of the toilet also need to be edited. Therefore, the designer requests inference of the element order to be edited for the toilet after changing the width of the toilet. At this time, if an element order that shortens the editing time is desired, the designer selects "editing time" as an index, and through steps S550 to S558, the created or edited element IDs are acquired from the CAD data currently being edited, and element order information is inferred and displayed from the acquired element IDs. In the inference, the first learning data of the knowledge base 54 is referenced by the selected AI model.

[0233] On the other hand, if an element order that reduces the number of edit items is desired, the designer selects "number of edit items" as an index, and through steps S550 to S558, created or edited element IDs are obtained from the CAD data currently being edited, and element order information is inferred and displayed from the obtained element IDs. In the inference, the second learning data in the knowledge base 54 is referenced by the selected AI model.

[0234] [Effects of this embodiment] Next, the effects of this embodiment will be described. In this embodiment, first learning data including an evaluation value based on the first index and second learning data including an evaluation value based on the second index are registered in the knowledge base 54, index information regarding the first index or the second index is obtained, and a request including a request to refer to either the first learning data or the second learning data in the knowledge base 54 based on the obtained index information is input to the AI ​​model 50.

[0235] This makes it possible to ascertain the order of elements with high evaluation values ​​based on the first index or the second index.

[0236] In this embodiment, step S402 corresponds to the registration means of invention 11 or 12, step S550 corresponds to the index information acquisition means of invention 12, steps S552 and S560 correspond to the element information acquisition means of invention 1, and steps S554 and S566 correspond to the input means of invention 1 or 12. Also, steps S556 and S568 correspond to the acquisition means of invention 1, and steps S558 and S570 correspond to the output means of invention 1.

[0237] [Modifications] In the above first to fourth embodiments and their variations, the first to fourth display rules are adopted, but the present invention is not limited to this. For example, a display rule that displays the element order with the fewest number of editing elements, a predetermined number or more, a predetermined number or less, or a predetermined rank, or any other display rule can be adopted.

[0238] Furthermore, in the above first to fourth embodiments and their variations, the element order is displayed according to one of a plurality of display rules, but this is not limited thereto, and the element order can be displayed according to a predetermined display rule without providing a plurality of display rules.

[0239] Furthermore, in the above first to fourth embodiments and their modifications, one element order is displayed, but the present invention is not limited to this and multiple element orders can be displayed.

[0240] Furthermore, in the above first to fourth embodiments and their modifications, the display rules are changed, but the present invention is not limited to this, and it is also possible to employ a configuration in which the display rules are not changed.

[0241] In the first and second embodiments and their modifications, the estimation and display are repeated multiple times, but the present invention is not limited to this, and it is also possible to adopt a configuration in which the estimation and display are performed only once. The same applies to the third and fourth embodiments and their modifications.

[0242] In addition, in the above first and second embodiments and their variations, reinforcement learning is adopted as the learning method, but this is not limited to this, and any learning method such as supervised learning, semi-supervised learning, unsupervised learning, deep learning, or any other learning method can be adopted.

[0243] In the first to fourth embodiments and their modifications, the learning data includes an already created or edited element ID, a plurality of edit elements edited in succession after the edit element and element order information related to the edit order, and an evaluation value related to the editing of the plurality of edit elements, but is not limited to this, and may be configured without including an evaluation value. In this case, the learning data includes an already created or edited element ID, a plurality of edit elements edited in succession after the edit element and element order information related to the edit order.

[0244] In addition, in the above first and second embodiments and their variations, the trained model used is one that has been trained based on created or edited element IDs, element order information, and evaluation values, but this is not limited to the above, and it is also possible to use one that has been trained based on created or edited element IDs and element order information.

[0245] In addition, in the above-described second embodiment and its modified example, the first trained model and the second trained model can be configured as one trained model.

[0246] In addition, in the third and fourth embodiments and their modifications, the AI ​​model 50 can be configured as the trained model in the first and second embodiments and their modifications.

[0247] In addition, in the above first to fourth embodiments and their modifications, an element order that appears a predetermined number of times or more in the learning data is identified. However, this is not limited to this, and it is also possible to identify an element order that appears a predetermined number of times or more in the editing history data.

[0248] In the above first to fourth embodiments and their modifications, a maximum of four editing elements and their editing orders are handled, but the present invention is not limited to this, and five or more editing elements and their editing orders can be handled. There is no need to limit the number of editing elements as long as there are multiple editing elements.

[0249] In the above first to fourth embodiments and their modifications, all combinations of element orders with 2 to 4 edit elements are obtained from the edit history data to generate learning data, but this is not limiting. It is also possible to obtain an element order that appears a predetermined number of times in the edit history data from the edit history data to generate learning data. In this case, an element order with a high frequency of appearance may be estimated using a trained model trained on a plurality of edit history data. This makes it possible to learn or infer an element order with a high frequency of appearance in the edit history data.

[0250] In the above first to fourth embodiments and their modifications, the edit history data is configured as data separate from the CAD data, but the present invention is not limited to this and may be configured as an integrated data included in the CAD data.

[0251] In the above third and fourth embodiments and their modifications, the learning data in the knowledge base 54 is referred to by the AI ​​model 50, but this is not limiting, and the learning data to be referred to in the knowledge base 54 can be included in the request. This makes it possible to apply the present invention to a configuration that does not include the knowledge base 54. Specifically, for example, the following configuration can be adopted.

[0252] [Invention A1] An element information acquisition means for acquiring element information relating to an element that has been created or edited in design information; an input means for inputting a request including a request for generating a plurality of element order information pieces each having different elements or different edit orders, the element order information pieces including the element information acquired by the element information acquisition means and relating to a plurality of elements and their edit orders that are edited consecutively after the element related to the element information (hereinafter, in Inventions A1 to A5, "a plurality of elements and their edit orders" will be referred to as "element order"); an acquisition means for acquiring the plurality of pieces of element order information output from the AI ​​model in response to the request; an output means for outputting one or more of the element orders based on the plurality of element order information acquired by the acquisition means, The request includes element information relating to an element that has been created or edited, and reference information including element order information relating to a number of elements to be edited successively after the element and the order in which they are edited.

[0253] This makes it possible to grasp a plurality of elements that are edited successively and the order of editing them.

[0254] [Invention A2] In Invention A1, The request includes element information on an element that has been created or edited, element order information on a plurality of elements to be edited successively after the element and the order of editing thereof, and reference information including evaluation values ​​related to the editing of the plurality of elements.

[0255] This makes it possible to grasp the order of elements with high evaluation values. As a modification of the third embodiment, embodiments of inventions A1 and A2 will be described. In step S502, a request for generating answer information is sent to the generation AI server 120. The request includes (1) the element ID acquired in step S500, (2) a generation request for generating element order information relating to a plurality of edit elements to be edited successively after an edit element that has already been created or edited and the order in which they are edited, (3) a selection request for selecting a predetermined AI model 50, and (4) the learning data acquired in step S400.

[0256] [Invention A3] In Invention A2, An index information acquisition means for acquiring index information on a first index indicating an index of the value of the evaluation value or a second index different from the first index, The input means inputs the request to the AI ​​model based on the index information acquired by the index information acquisition means, the request including either first reference information including the element information, the element order information, and the evaluation value based on the first index, or second reference information including the element information, the element order information, and the evaluation value based on the second index.

[0257] This makes it possible to ascertain the order of elements with high evaluation values ​​based on the first index or the second index.

[0258] An embodiment of the invention A3 will be described as a modification of the above fourth embodiment. In step S554, a request for generating answer information is sent to the generation AI server 120. The request includes (1) the element ID acquired in step S552, (2) a generation request for generating multiple edit elements to be edited next to the edit element that has already been created or edited and element order information related to the edit order, (3) a selection request for selecting a predetermined AI model 50, and (4) the first learning data acquired in step S400 if the index related to the index information acquired in step S550 is the first index, or the second learning data acquired in step S400 if the index related to the index information acquired in step S550 is the second index.

[0259] [Invention A4] In Inventions A1 to A3, The multiple elements are elements that require human judgment to set or change, and the setting or change has an effect on other elements.

[0260] [Invention A5] In Inventions A1 to A3, The design information is information for designing a building.

[0261] In the third and fourth embodiments and their modifications, the AI ​​model 50 refers to the information in the knowledge base 54, but the present invention is not limited to this. Information to be referred to in the knowledge base 54 (for example, the learning data in FIG. 5 or FIG. 11) can be obtained by a Web search or the like, and the search results can be referred to by the AI ​​model 50 to perform inference. This configuration can be realized, for example, by RAG (Retrieval Augmented Generation).

[0262] Furthermore, in the above first to fourth embodiments and their modifications, the trained model or AI model 50 is used, but the present invention is not limited to this, and for example, the following configuration may be adopted.

[0263] [Invention B1] An element information acquisition means for acquiring element information relating to an element that has been created or edited in design information; a search means for searching, from a storage means for storing element order information relating to a plurality of elements to be edited next to an already created or edited element and their edit order (hereinafter, in Inventions B1 to B14, "a plurality of elements and their edit order" will be referred to as "element order") in association with element information relating to the already created or edited element, for a plurality of pieces of element order information with different elements or edit orders corresponding to the element information acquired by the element information acquisition means; and an output means for outputting one or more of the element orders based on the plurality of pieces of element order information retrieved by the search means.

[0264] As a result, one or more element sequences are output, so that it is possible to grasp a plurality of elements that are edited successively and the sequence of editing thereof.

[0265] [Invention B2] In Invention B1, The output means outputs the element sequence having the largest number of elements from among the plurality of element sequences.

[0266] This allows editing to be performed while imagining larger editing units. [Invention B3] In Invention B1, an identification means for identifying the element sequence having a predetermined number of occurrences or more in the design information as a related group; The output means outputs an element sequence having the associated grouping identified by the identification means, from among the plurality of element sequences.

[0267] This allows you to edit while imagining related groups. [Invention B4] In Invention B3, The output means outputs, from among the plurality of element orders, an element order that is the same as the associated group identified by the identification means.

[0268] [Invention B5] In Invention B1, an identification means for identifying the element sequence having a predetermined number of occurrences or more in the design information as a related group; The output means outputs a portion of the related group identified by the identification means from an element sequence including the related group and other elements, out of the plurality of element sequences.

[0269] This allows you to edit while imagining related groups. [Invention B6] In Inventions B1 to B5, a second element information acquisition means for acquiring element information relating to an element that has been created or edited based on the element order output by the output means; The device further includes a second search means for searching the storage means for a plurality of pieces of element order information having different elements or editing orders corresponding to the element information acquired by the second element information acquisition means.

[0270] This makes it possible to obtain a plurality of pieces of element order information for the results of creation or editing based on the output element order, so that a plurality of elements that are edited consecutively and their editing order can be grasped.

[0271] [Invention B7] In Inventions B1 to B5, a second element information acquisition means for acquiring element information relating to an element that has been created or edited based on the element order output by the output means; and an estimation means for estimating a plurality of pieces of element order information having different elements or editing orders from the element information acquired by the second element information acquisition means, using a trained model trained based on training data including element information on an element that has been created or edited, and element order information on a plurality of elements edited consecutively after the element and their editing order.

[0272] This makes it possible to obtain a plurality of pieces of element order information for the results of creation or editing based on the output element order, so that a plurality of elements that are edited consecutively and their editing order can be grasped.

[0273] [Invention B8] In Inventions B1 to B5, an input means for inputting a request including a request for generating a plurality of element order information pieces each including the element information acquired by the second element information acquisition means, the element order information pieces each including a plurality of elements to be edited successively after the element related to the element information and an order of editing the plurality of elements, the plurality of element order information pieces each including a different element or editing order; and an acquisition means for acquiring the plurality of element order information output from the AI ​​model in response to the request.

[0274] This makes it possible to obtain a plurality of pieces of element order information for the results of creation or editing based on the output element order, so that a plurality of elements that are edited consecutively and their editing order can be grasped.

[0275] [Invention B9] In Inventions B1 to B5, a second element information acquisition means for acquiring element information relating to an element that has been created or edited based on the element order output by the output means; and an output rule changing means for changing an output rule of the output means based on the element order output by the output means and the element information acquired by the second element information acquiring means.

[0276] This makes it possible to change the output rule according to the output result of the output means and the result of subsequent creation or editing.

[0277] [Invention B10] In Invention B1, the storage means stores element order information relating to a plurality of elements to be edited successively after an element that has already been created or edited and an order of editing thereof, in association with element information relating to the created or edited element and an evaluation value relating to editing of the plurality of elements; The search means searches for a plurality of pieces of element order information corresponding to the element information acquired by the element information acquisition means and having the evaluation value equal to or greater than a predetermined value.

[0278] This makes it possible to grasp the order of elements with high evaluation values. As a modification of the first embodiment, embodiments of inventions B1 and B10 will be described. Storage device 42 stores an element order information table having a data structure similar to that of the learning data in Fig. 5. In step S302, the element order information table is searched for a plurality of pieces of element order information corresponding to the element ID acquired in step S300 and having an evaluation value of a predetermined value or more. In step S312, the element order information table is searched for a plurality of pieces of element order information corresponding to the element ID acquired in step S306 and having an evaluation value of a predetermined value or more.

[0279] [Invention B11] In Invention B10, the storage means includes a first storage means for storing the element order information in association with the element information and the evaluation value based on a first index indicating an index of value of the evaluation value, and a second storage means for storing the element order information in association with the element information and the evaluation value based on a second index different from the first index; An index information acquisition means for acquiring index information relating to the first index or the second index; a storage means selection means for selecting either the first storage means or the second storage means based on the index information acquired by the index information acquisition means, The retrieval means retrieves a plurality of pieces of element order information from the storage means selected by the storage means selection means.

[0280] This makes it possible to ascertain the order of elements with high evaluation values ​​based on the first index or the second index.

[0281] An embodiment of the invention B11 will be described as a modification of the second embodiment. The storage device 42 stores a first element order information table having a data structure similar to that of the learning data in FIG. 5, and a second element order information table having a data structure similar to that of the learning data in FIG. 11. In step S352, if the index related to the index information acquired in step S350 is the first index, the first element order information table is selected, and if the index related to the acquired index information is the second index, the second element order information table is selected. In step S356, a plurality of element order information corresponding to the element ID acquired in step S354 and having an evaluation value of a predetermined value or more is searched from the element order information table selected in step S352. In step S366, a plurality of element order information corresponding to the element ID acquired in step S360 and having an evaluation value of a predetermined value or more is searched from the element order information table selected in step S352.

[0282] [Invention B12] In Invention B10, the storage means stores the element information, the element order information, the evaluation value based on a first index indicating an index of value of the evaluation value, and index information related to the first index in association with each other, and also stores the element information, the element order information, the evaluation value based on a second index different from the first index, and index information related to the second index in association with each other; An index information acquisition means for acquiring index information relating to the first index or the second index, The search means searches for a plurality of pieces of element order information corresponding to the element information acquired by the element information acquisition means and the index information acquired by the index information acquisition means, the element order information having an evaluation value equal to or greater than a predetermined value.

[0283] This makes it possible to ascertain the order of elements with high evaluation values ​​based on the first index or the second index.

[0284] An embodiment of the invention B12 will be described as a modification of the second embodiment. The storage device 42 stores an element order information table in which (1) created or edited element ID 410, element order information 412, evaluation value 414, and index information related to the first index, or (2) created or edited element ID 416, element order information 418, evaluation value 420, and index information related to the second index are registered for each row. In step S356, the element order information table is searched for a plurality of element order information corresponding to the element ID acquired in step S354 and the index information acquired in step S350, and having an evaluation value of a predetermined value or more. In step S366, the element order information table is searched for a plurality of element order information corresponding to the element ID acquired in step S360 and the index information acquired in step S350, and having an evaluation value of a predetermined value or more.

[0285] [Invention B13] In Inventions B1 to B5, The multiple elements are elements that require human judgment to set or change, and the setting or change has an effect on other elements.

[0286] [Invention B14] In Inventions B1 to B5, The design information is information for designing a building.

[0287] In addition, in inventions B1 to B14 and their variations, storing element order information in association with element information, etc. includes, for example, (1) storing element order information and element information, etc. in the same record in a direct association manner, and (2) storing via one or more pieces of intermediate information, such as providing a table in which element order information and intermediate information are associated and registered, and a table in which element information, etc. and intermediate information are associated and registered. In other words, any data structure can be adopted as long as the element order information can be traced from the element information, etc. Note that it is sufficient for the element order information to be stored in a storage means in association with the element information, etc., and it is not necessarily required to store the element information, etc. in the storage means.

[0288] Furthermore, in inventions B1 to B14 and their variations, the storage means stores the element order information by any means and at any time, and may store the element order information in advance, or may store the element order information by external input or the like during operation of drawing creation support device 100 without storing the element order information in advance.

[0289] Furthermore, in the third and fourth embodiments and their variations, the prompt is, for example, a request to the AI ​​model 50 to generate, based on the created or edited element ID, a plurality of edit elements to be edited in succession after a created or edited edit element and element order information regarding the edit order thereof, the plurality of edit elements having an evaluation value equal to or greater than a predetermined value. However, without being limited to this, the prompt may be a request to the AI ​​model 50 to generate a plurality of edit elements to be edited in succession after a created or edited edit element and element order information regarding the edit order thereof.

[0290] 5 or 11 is registered in the knowledge base 54 in the third and fourth embodiments and their modifications. However, the present invention is not limited to this. (1) Edit history data, (2) Reference information including element information on an element that has already been created or edited, and element order information on a plurality of elements to be edited in succession after the element and the order of editing thereof, or (3) Reference information including element information on an element that has already been created or edited, element order information on a plurality of elements to be edited in succession after the element and the order of editing thereof, and evaluation values ​​related to the editing of the plurality of elements may be registered in the knowledge base 54. The reference information of (2) or (3) may include element order information estimated using the trained model in the first and second embodiments and their modifications.

[0291] Furthermore, in the third and fourth embodiments and their modifications, vector data is registered in the knowledge base 54, but the present invention is not limited to this and data in any format can be registered.

[0292] In addition, in the above first to fourth embodiments and their modifications, a configuration including any one of an estimation process using a trained model, an acquisition process from the AI ​​model 50, and a search process using a table is adopted, but the present invention is not limited to this, and a configuration including two or more of these processes can be adopted. Specifically, for example, the following configuration can be adopted.

[0293] The first configuration is a configuration in which the process of step S302 or the process of step S312 is performed by any one of an estimation process, an acquisition process, and a search process. The second and subsequent processes of step S312 can be performed by the same or different processes as the process of step S302 or the first process of step S312.

[0294] In the second configuration, the process of step S356 or the process of step S366 is performed by any one of an estimation process, an acquisition process, and a search process. The process of step S366 from the second time onwards can be performed by the same or different process as the process of step S356 or the process of step S366 for the first time.

[0295] In the third configuration, the processes of steps S502 and S504 or steps S514 and S516 are performed by any one of estimation processes, acquisition processes, and search processes. The processes of steps S514 and S516 from the second time onwards can be performed by the same or different processes as the processes of steps S502 and S504 or the first time of steps S514 and S516.

[0296] In the fourth configuration, the processes of steps S554 and S556 or the processes of steps S566 and S568 are performed by any one of estimation processes, acquisition processes, and search processes. The processes of steps S566 and S568 from the second time onwards can be performed by the same or different processes as the processes of steps S554 and S556 or the first time of steps S566 and S568.

[0297] The fifth configuration is a configuration for controlling which process is given priority. For example, it is possible to adopt (1) a configuration for giving priority to a process with a low current load among a plurality of processes, (2) a configuration for giving priority to a process whose results have been adopted by designers to a high degree (referring to the number of times of adoption, the percentage, or other degree), or (3) a configuration for giving priority to a process whose results have been used by designers to a high degree (referring to the number of times of use, the percentage, or other degree).

[0298] Furthermore, in the above first to fourth embodiments and their modified examples, multiple edit elements and their edit order are learned or inferred, but the present invention is not limited to this. The "multiple edit elements" to be learned or inferred can be edit element A, the setting or change of which requires human judgment, and the setting or change of which has an effect on another edit element B. This makes it possible to grasp the element order taking into consideration the relationship between edit element A and edit element B. For edit elements that do not require human judgment, editing can be automated using the technology of Japanese Patent No. 7341580, for example, so that editing work can be made more efficient by targeting edit elements that are difficult to automate.

[0299] In the first and second embodiments and their modifications, the device is realized as a single device, but the present invention is not limited to this, and may be realized as a network system. As an example of a network system, a part or all of the functions of the drawing creation support device 100 may be configured as a virtual server on a server that provides a cloud computing service.

[0300] Furthermore, in the above third and fourth embodiments and their variations, the generation AI server 120 is configured as an integrated unit that includes the functions of the AI ​​model 50, the AI ​​model control unit 52, the knowledge base 54, the request receiving unit 56, the request processing unit 58, the answer information sending unit 60, the request receiving unit 62, and the learning data registration unit 64, but this is not limited to the above, and some of the functions may be configured as separate servers, etc.

[0301] Furthermore, in the third and fourth embodiments and the modifications thereof, the system is realized as a network system, but the present invention is not limited to this and may be realized as a single device or application.

[0302] In addition, in the above third and fourth embodiments and their modifications, the case where the present invention is applied to a network system consisting of the Internet 199 has been described, but the present invention is not limited to this, and may be applied to, for example, a so-called intranet that communicates in the same manner as the Internet 199. Of course, the present invention is not limited to a network that communicates in the same manner as the Internet 199, and may be applied to a network of any communication method.

[0303] Furthermore, in the above first to fourth embodiments and their variations, the drawing creation support device 100 is configured to use the storage device 42, but this is not limited to this and it can also be configured to use an external storage device such as a database server.

[0304] In addition, in the above first to fourth embodiments and their variations, when executing the processes shown in the flowcharts of Figures 4, 6, 8, 12, 15, 16 and 17, a program pre-stored in ROM 32 is executed. However, this is not limited to the above, and the program showing these procedures may be read into RAM 34 from a storage medium on which the program is stored and executed.

[0305] Here, storage media refers to semiconductor storage media such as RAM and ROM, magnetic storage type storage media such as FD and HD, optically readable storage media such as CD, CDV, LD and DVD, and magnetic storage type / optically readable storage media such as MO, and includes any storage medium that can be read by a computer, regardless of the reading method (electronic, magnetic, optical, etc.).

[0306] Moreover, the above first to fourth embodiments and their modifications can be applied to each other. Furthermore, the present invention is not limited to the first to fourth embodiments and their modifications, but may be applied to other cases without departing from the spirit of the present invention. For example, the present invention may be applied to a wide range of design cases, such as automobile design, machine design, and circuit design. [Explanation of symbols]

[0307] 100...Drawing creation support device, 30...CPU, 32...ROM, 34...RAM, 38...I / F, 39...bus, 40...input device, 42...storage device, 44...display device, 120...generation AI server, 50...AI model, 52...AI model control unit, 54...knowledge base, 56, 62...request receiving unit, 58...request processing unit, 60...answer information sending unit, 64...learning data registration unit, 199...Internet, 400, 404...element information, 402...editing time, 406...number of edited items, 410, 416...element ID, 412, 418...element order information, 414, 420...evaluation value

Claims

1. An element information acquisition means for acquiring element information relating to an element that has been created or edited in the design information; An input means for inputting a request including a request for generating a plurality of element order information pieces each including the element information acquired by the element information acquisition means, the element order information pieces each including a plurality of elements to be edited in succession following the element related to the element information and the order of the elements to be edited (hereinafter, the "plural elements and the order of the elements to be edited" will be referred to as "element order"). The element order information pieces each including a plurality of elements or an order of the elements to be edited will be referred to as "element order". An acquisition means for acquiring the plurality of element order information output from the AI ​​model in response to the request; an output unit that outputs one or more of the element orders based on the plurality of element order information acquired by the acquisition unit.

2. In claim 1, The design support system is characterized in that the output means outputs the element sequence having the largest number of elements from among the plurality of element sequences.

3. In claim 1, an identification means for identifying the element sequence having a predetermined number of occurrences or more in the design information as a related group; The design support system according to claim 1, wherein the output means outputs an element sequence having the associated grouping identified by the identifying means from among the plurality of element sequences.

4. In claim 3, The design support system according to claim 1, wherein the output means outputs an element sequence identical to the related group identified by the identification means, from among the plurality of element sequences.

5. In claim 1, an identification means for identifying the element sequence having a predetermined number of occurrences or more in the design information as a related group; The design support system is characterized in that the output means outputs a related portion of the element sequences identified by the identification means from among the multiple element sequences, the related portion being a group of elements identified by the identification means and an element sequence including other elements.

6. In any one of claims 1 to 5, a second element information acquiring means for acquiring element information relating to an element that has been created or edited based on the element order output by the output means; A second input means for inputting a request including a request to generate a plurality of element order information including the element information acquired by the second element information acquisition means, the element order information being related to a plurality of elements to be edited successively after the element related to the element information and the order of editing thereof, the plurality of element order information including a request to generate a plurality of element order information including different elements or different editing orders; A design support system comprising: a second acquisition means for acquiring the plurality of element order information output from the AI ​​model in response to the request.

7. In any one of claims 1 to 5, a second element information acquiring means for acquiring element information relating to an element that has been created or edited based on the element order output by the output means; and an estimation means for estimating a plurality of pieces of element order information having different elements or edit orders from the element information acquired by the second element information acquisition means, using a trained model trained based on training data including element information on an element that has been created or edited, and element order information on a plurality of elements that have been edited in succession after the element and their edit order.

8. In any one of claims 1 to 5, a second element information acquiring means for acquiring element information relating to an element that has been created or edited based on the element order output by the output means; a search means for searching, from a storage means for storing element order information relating to a plurality of elements to be edited successively after an element that has already been created or edited and the order of editing of the elements, in correspondence with element information relating to the created or edited element, for a plurality of pieces of element order information having different elements or editing orders that correspond to the element information acquired by the second element information acquisition means.

9. In any one of claims 1 to 5, a second element information acquiring means for acquiring element information relating to an element that has been created or edited based on the element order output by the output means; a second element information acquisition means for acquiring element information from the second element information acquisition means; and an output rule change means for changing an output rule of the output means based on the element order output by the output means and the element information acquired by the second element information acquisition means.

10. In claim 1, A registration means for registering reference information including element information on an element that has been created or edited, and element order information on a plurality of elements to be edited successively next to the element and an order of editing thereof, in a knowledge base that can be referenced by the AI ​​model; A design support system characterized in that the acquisition means acquires the plurality of element order information output from the AI ​​model by referring to reference information in the knowledge base in response to the request.

11. In claim 10, The design support system is characterized in that the registration means registers in the knowledge base element information relating to an element that has been created or edited, element order information relating to a plurality of elements to be edited successively after the element in question and the order in which they are edited, and reference information including evaluation values ​​relating to the editing of the plurality of elements.

12. In claim 11, the registration means registers, in the knowledge base, first reference information including the element information, the element order information, and the evaluation value based on a first index indicating an index of value of the evaluation value, and second reference information including the element information, the element order information, and the evaluation value based on a second index different from the first index; An index information acquisition means for acquiring index information relating to the first index or the second index, A design support system characterized in that the input means inputs the request, including a request to refer to either the first reference information or the second reference information of the knowledge base, to the AI ​​model based on the index information acquired by the index information acquisition means.

13. In claim 1, A design support system characterized in that the request includes element information regarding an element that has already been created or edited, and reference information including element order information regarding a plurality of elements to be edited successively after the element and the order in which they are edited.

14. In claim 13, A design support system characterized in that the request includes element information regarding an element that has already been created or edited, element order information regarding a plurality of elements to be edited successively after the element and the order in which they are edited, and reference information including evaluation values ​​regarding the editing of the plurality of elements.

15. In claim 14, An index information acquisition means for acquiring index information relating to a first index indicating an index of the value of the evaluation value or a second index different from the first index, The design support system is characterized in that the input means inputs the request to the AI ​​model based on the index information acquired by the index information acquisition means, the request including either first reference information including the element information, the element order information, and the evaluation value based on the first index, or second reference information including the element information, the element order information, and the evaluation value based on the second index.

16. In any one of claims 1 to 5, A design support system, wherein the plurality of elements are elements whose setting or change requires human judgment and whose setting or change has an effect on other elements.

17. In any one of claims 1 to 5, A design support system, wherein the design information is design information for designing a building.

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