Method for recommending models of equipment components, controllers and media based on weighting

Abstract

The present invention discloses a method, controller and medium for recommending models of equipment components based on weighting. The recommendation method includes obtaining historical data of a distribution network, obtaining a target recommended value of the model of the equipment component according to the historical data; obtaining a target model of the equipment component according to the target recommended value, and recommending the target model; obtaining the target recommended value of the model of the equipment component according to the historical data includes obtaining a first recommended value of the model of the equipment component, the first recommended value includes a recommended value obtained according to the price of the model of the equipment component; obtaining a second recommended value of the model of the equipment component according to the number of times the equipment component of the same model is used in the historical data; obtaining the location information of the equipment component to be selected, and obtaining a third recommended value of the model of the equipment component according to the location information; obtaining the target recommended value of the model of the equipment component according to the first recommended value, the second recommended value and the third recommended value, so as to achieve the purpose of reasonably recommending the model of the equipment component.

Description

Technical Field

[0001] The present invention relates to the field of recommendation technology, and in particular to a method, a controller and a medium for recommending models of equipment components based on weighting. Background Art

[0002] The economic losses and social impact caused by power quality problems and power outages in my country are increasing. High reliability and high quality electricity have become important basic conditions for creating high-quality products, attracting domestic and foreign capital, and promoting industrial structure optimization and upgrading. When planning distribution network sites, it is generally necessary to reasonably select distribution network equipment based on actual conditions. However, in actual drawing work, due to the rich and diverse models of equipment components on the market, it takes a lot of time to select models. Therefore, how to improve the efficiency of selection and thus improve the efficiency of drawing is a major technical problem. Summary of the invention

[0003] The purpose of the present invention is to solve at least one of the technical problems existing in the prior art and to provide a weighted device component recommendation method that can recommend device component models and improve drawing efficiency.

[0004] In a first aspect, an embodiment of the present invention provides a method for recommending a model of a device component based on weighting, comprising:

[0005] Obtain historical data of the distribution network;

[0006] Obtaining a target recommended value for the model of the equipment component according to the historical data;

[0007] Obtaining a target model of the device component according to the target recommendation value, wherein the target recommendation value of the target model is greater than the target recommendation value of the non-target model;

[0008] recommending the target model;

[0009] The step of obtaining a target recommended value for the model of the device component according to the historical data includes:

[0010] Acquire a first recommended value of the model of the device component, wherein the first recommended value includes: a recommended value obtained according to a price of the model of the device component;

[0011] Obtaining the number of times the device component having the same model is used according to the historical data, and obtaining a second recommended value for the model of the device component according to the number of times used;

[0012] Acquire location information of a device component to be selected, and obtain a third recommended value of a model of the device component according to the location information;

[0013] A target recommended value for the model of the device component is obtained according to the first recommended value, the second recommended value and the third recommended value.

[0014] The weighted device component recommendation method according to the embodiment of the present invention has at least the following beneficial effects: historical data of the distribution network is obtained, and the historical data may include data such as the name, model, and number of times of use of the device components that appear in the historical drawing, and the device components in the historical data can obtain the corresponding model data. The target recommended value of the device component is obtained according to the historical data, which may be a first recommended value of the model of the device component, the first recommended value includes a recommended value obtained according to the price of the model of the device component, and the first recommended value may be preset by the user, so that the target recommended value is more in line with the actual usage. The second recommended value of the model is obtained according to the number of times the device components of the same model are used recorded in the historical data, and the position information of the device component to be selected is obtained. The device component to be selected refers to the device component that does not have a model in the drawing, and the third recommended value of the model is obtained according to the position information. The position information may be the distance value between the device component to be selected and any other device component, or may be the specific position information of the device component to be selected in the distribution network. The third recommended value utilizes the position information of the device component to be selected, which can improve the rationality of the target recommended value. The target recommended value of the device component is obtained according to the first recommended value, the second recommended value and the third recommended value. The target recommended value of the model of the device component can be obtained by adding the recommended values ​​or multiplying the recommended values ​​by the weight preset by the user, which plays a role in improving the rationality of the target recommended value. Finally, according to the target recommended value, the model of the device component with a high target recommended value is selected as the target model, and the target model is recommended. The method of this embodiment can reasonably recommend the model of the device component according to the target recommended value, which plays a role in improving the drawing efficiency.

[0015] According to some embodiments of the present invention, obtaining a target model according to the target recommendation value includes:

[0016] The models of the equipment components in the historical data are sorted according to the target recommendation value to obtain the target model.

[0017] According to some embodiments of the present invention, the first recommended value further includes:

[0018] The recommended value is obtained based on the preset stability factor of the model of the equipment component.

[0019] According to some embodiments of the present invention, obtaining a second recommended value of the model of the device component according to the number of uses includes:

[0020] The second recommendation value is obtained by multiplying the number of times of use by a preset weight of the number of times of use.

[0021] According to some embodiments of the present invention, obtaining a third recommended value of the model of the device component according to the location information includes:

[0022] Acquire a first position of the device component to be selected;

[0023] Acquire a second position of an adjacent equipment component connected to the equipment component to be selected;

[0024] forming a first matrix according to a first distance between the first position and the second position;

[0025] Acquire a second distance between the neighboring device element and the device element in the historical data, and form a second matrix according to the second distance, wherein the dimension of the second matrix is ​​equal to the dimension of the first matrix;

[0026] A third recommended value of the model of the device component is obtained according to the distance value between the first matrix and the second matrix.

[0027] According to some embodiments of the present invention, obtaining a third recommended value of the model of the device component according to the location information further includes:

[0028] A distance threshold is set for reducing the complexity of the first matrix, wherein the first distance is less than or equal to the distance threshold.

[0029] According to some embodiments of the present invention, obtaining the second distance between the neighboring device element and the device element in the historical data includes:

[0030] When the neighboring device component is not connected to the device component in the historical data, the third recommended value of the model of the device component in the historical data is lowered.

[0031] According to some embodiments of the present invention, obtaining the second distance between the neighboring device element and the device element in the historical data includes:

[0032] When the second distance is greater than the distance threshold, a third recommended value of the model of the equipment component in the historical data is reduced.

[0033] In a second aspect, an embodiment of the present invention provides a controller comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the weighted device component model recommendation method of the first aspect when executing the computer program.

[0034] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the method for recommending a model of a device component based on weighting according to the first aspect.

[0035] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the technical solution of the present invention and do not constitute a limitation on the technical solution of the present invention.

[0037] The present invention is further described below in conjunction with the accompanying drawings and embodiments;

[0038] Figure 1 is a flowchart of a method for recommending a model of a device component based on weighting provided by an embodiment of the present invention;

[0039] Figure 2 is a flowchart of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention;

[0040] Figure 3 is a flowchart of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention;

[0041] Figure 4 is a flowchart of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention;

[0042] Figure 5 is a flowchart of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention;

[0043] Figure 6 is a flowchart of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention;

[0044] Figure 7 is a flowchart of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention;

[0045] Figure 8 is a flowchart of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention;

[0046] Fig. 9 It is a flowchart of the steps of another method for recommending models of equipment components based on weighting provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] This section will describe in detail the specific embodiments of the present invention. The preferred embodiments of the present invention are shown in the accompanying drawings. The purpose of the accompanying drawings is to supplement the description of the text part of the specification with graphics, so that people can intuitively and vividly understand each technical feature and the overall technical solution of the present invention, but it cannot be understood as a limitation on the scope of protection of the present invention.

[0048] In the description of the present invention, if there is a description of first and second, it is only for the purpose of distinguishing the technical features, and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0049] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0050] The embodiment of the present invention provides a method, controller and medium for recommending the model of equipment components based on weighting. The recommendation method includes obtaining historical data of a distribution network, and the historical data may include data such as the name, model and number of times of use of equipment components appearing in historical drawing. The equipment components in the historical data can obtain corresponding model data. The target recommended value of the equipment component is obtained according to the historical data, which may be a first recommended value of the model of the equipment component. The first recommended value includes a recommended value obtained according to the price of the model of the equipment component. The first recommended value may be preset by the user to achieve the effect that the target recommended value is more in line with the actual usage. The second recommended value of the model is obtained according to the number of times of use of equipment components of the same model recorded in the historical data, and the position information of the equipment component to be selected is obtained. The equipment component to be selected refers to the equipment component that does not have a model in the drawing. The third recommended value of the model is obtained according to the position information. The position information may be the distance value between the equipment component to be selected and any other equipment component, or may be the specific position information of the equipment component to be selected in the distribution network. The third recommended value utilizes the position information of the equipment component to be selected, which can improve the rationality of the target recommended value. The target recommended value of the device component is obtained according to the first recommended value, the second recommended value and the third recommended value. The target recommended value of the model of the device component can be obtained by adding the recommended values ​​or multiplying the recommended values ​​by the weight preset by the user, which plays a role in improving the rationality of the target recommended value. Finally, according to the target recommended value, the model of the device component with a high target recommended value is selected as the target model, and the target model is recommended. The method of this embodiment can reasonably recommend the model of the device component according to the target recommended value, which plays a role in improving the drawing efficiency.

[0051] The embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0052] Reference Figure 1 and Figure 2 The first aspect of the present invention provides a method for recommending models of equipment components based on weighting, which may include but is not limited to steps S110 to S140 and steps S121 to S124.

[0053] Step S110: Acquire historical data of the distribution network;

[0054] In this step, the historical data of the distribution network may include data such as the name, model, and usage count of the equipment components that appear during the historical drawing, and the equipment components in the historical data may obtain corresponding model data.

[0055] It is understandable that the historical data of the distribution network may be stored in any memory, and the historical data of the distribution network is obtained for use in subsequent steps.

[0056] Step S120: obtaining a target recommended value of a model of a device component according to historical data;

[0057] Step S120 includes but is not limited to the following steps:

[0058] Step S121: obtaining a first recommended value of a model of a device component, wherein the first recommended value includes a recommended value obtained according to a price of the model of the device component;

[0059] In this step, the first recommended value includes a recommended value obtained based on the price of the model of the equipment component. The first recommended value can be a recommended value obtained by comparing the prices of various models of the equipment component, or it can be a recommended value preset by any user in the relevant technology or related to actual use, such as: the durability of the model, the stability coefficient of the model, etc.

[0060] In an optional embodiment, the first recommended value can be obtained by first counting the prices of various models of equipment components and then obtaining a recommended value based on the price. The recommended value is the first recommended value. The first recommended value can be equal to the price, or it can be obtained by multiplying the price with a preset price coefficient.

[0061] Step S122: obtaining the usage count of the equipment component with the same model according to the historical data, and obtaining a second recommended value of the model of the equipment component according to the usage count;

[0062] In this step, the usage count of the equipment components with the same model is obtained according to the historical data, which can be done by extracting the equipment components with the same model from the historical data, and then counting the number of times the equipment components appear to obtain the usage count of the equipment components. A second recommended value of the model of the equipment component is obtained according to the usage count, and the second recommended value depends on the usage count of the model, which can achieve the effect of improving the recommendation accuracy.

[0063] Step S123: Acquire the position information of the equipment component to be selected, and obtain a third recommended value of the model of the equipment component according to the position information;

[0064] In this step, the device component to be selected refers to the device component whose model has not yet been determined in the current drawing. The position information of the device component to be selected can be the position information of the device component in the drawing, or the specific coordinate information of the device component to be selected. The position information can be obtained through the position relationship or connection relationship between the device component and other components, and the third recommended value of the model of the device component is obtained according to the position information.

[0065] Step S124: Obtain a target recommended value for the model of the device component according to the first recommended value, the second recommended value, and the third recommended value.

[0066] In this step, the target recommended value of the model of the equipment component is obtained according to the first recommended value, the second recommended value and the third recommended value. The target recommended value can be obtained by directly adding the first recommended value, the second recommended value and the third recommended value, or weights can be set here to multiply the first recommended value, the second recommended value and the third recommended value by the corresponding weight values ​​to obtain the target recommended value.

[0067] Step S130: obtaining a target model of the device component according to the target recommendation value, wherein the target recommendation value of the target model is greater than the target recommendation value of the non-target model;

[0068] In this step, the target model of the equipment component is obtained according to the target recommendation value. The target model refers to the model of the equipment component with a higher target recommendation value. The target recommendation value of the target model is greater than the target recommendation value of the non-target model. The number of target models can be any number and is not limited in this embodiment.

[0069] Step S140: recommending the target model;

[0070] In this step, recommending the target model refers to recommending the target model to the current drawing interface. In an optional implementation, during the selection process, the target model is recommended to the vicinity of the corresponding device component for selection.

[0071] In this embodiment, by adopting the above steps S110 to S140 and S121 to S124, historical data of the distribution network is obtained, and the target recommended value of the equipment component is obtained according to the historical data. The first recommended value of the model of the equipment component can be obtained, and the first recommended value includes a recommended value obtained according to the price of the model of the equipment component. The second recommended value of the model is obtained according to the number of times the equipment component of the same model is used recorded in the historical data, and the location information of the equipment component to be selected is obtained. The third recommended value of the model is obtained according to the location information. The third recommended value utilizes the location information of the equipment component to be selected, which can improve the rationality of the target recommended value. The target recommended value of the equipment component is obtained according to the first recommended value, the second recommended value and the third recommended value. Finally, according to the target recommended value, the model of the equipment component with a high target recommended value is selected as the target model, and the target model is recommended to achieve the purpose of improving drawing efficiency.

[0072] In one embodiment, if Figure 3 As shown, step S130 is further explained, and the step may also include but is not limited to step S131.

[0073] Step S131: sorting the models of equipment components in the historical data according to the target recommendation value to obtain the target model.

[0074] In this step, the models of the equipment components in the historical data are sorted according to the target recommendation values, and the models of the obtained equipment components are ordered. The models with large target recommendation values ​​are selected as the target models according to the order, so as to achieve the purpose of facilitating the selection of the target models.

[0075] It should be noted that the sorting may be any sorting method in the related art, such as bubble sort, selection sort, etc., as long as it can enable the device components to sort the models according to the target recommended values, and is not limited in this embodiment.

[0076] In this embodiment, through step S131, the models of equipment components in the historical data are sorted according to the target recommendation value to obtain the target model, thereby achieving the purpose of facilitating the selection of the target model.

[0077] In one embodiment, if Figure 4 As shown, step S121 is further explained, and the step includes but is not limited to step S1211.

[0078] Step S1211: The first recommended value also includes: a recommended value obtained according to the stability coefficient of the model of the equipment component.

[0079] In this step, the stability coefficient may be assigned according to the stability of the equipment component. When selecting the equipment component, the stability of the equipment component may be used as a weight to set a recommended value, so as to achieve the purpose of making the recommended equipment component model more reasonable.

[0080] In this embodiment, through step S1211, the first recommended value also includes: a recommended value obtained according to the stability coefficient of the model of the equipment component, and the stability of the equipment component is used as a weight to achieve the purpose of making the recommended model of the equipment component more reasonable.

[0081] In one embodiment, if Figure 5 As shown, step S122 is further described, which includes but is not limited to step S1221.

[0082] Step S1221: multiply the number of times of use by a preset weight of the number of times of use to obtain a second recommendation value.

[0083] In this step, the preset weight of the number of times of use may be preset according to the total number of times of use in the historical data, or may be preset according to the importance of the number of times of use in the recommendation.

[0084] It should be noted that the value of the second recommended value may be equal to the number of times of use.

[0085] In this embodiment, through step S1221, the number of times of use is multiplied by a preset weight of the number of times of use to obtain a second recommended value, so as to achieve the purpose of reducing or increasing the influence of the second recommended value on the target recommended value.

[0086] In one embodiment, if Figure 6 As shown, step S123 is further described, which includes but is not limited to steps S1231 to S1235.

[0087] Step S1231: Obtain the first position of the equipment component to be selected.

[0088] In this step, the device components to be selected refer to the device components that have not been selected in the current drawing, that is, the device components to be selected are the device components that are currently waiting for the recommended model.

[0089] It should be noted that obtaining the first position of the device component to be selected refers to obtaining the position of the device component to be selected in the drawing, which may be a specific coordinate position or a relative position obtained through a front-to-back connection relationship.

[0090] Step S1232: Acquire the second position of the adjacent equipment component connected to the equipment component to be selected.

[0091] In this step, the adjacent device element refers to a device element connected to the device element to be selected, and may be a device element of the same type as the device element to be selected, or may be a device element of a different type from the device element to be selected, which is not specifically limited in this embodiment.

[0092] It should be noted that obtaining the second position of the adjacent device element may be obtaining the position of the adjacent device element in the drawing, which may be a specific coordinate position, or a relative position obtained through a front-to-back connection relationship.

[0093] Step S1233: forming a first matrix according to the first distance between the first position and the second position.

[0094] In this step, the first distance refers to the shortest distance between the first position and the second position. The first distance can be represented by the distance from the first position to the second position. In an optional embodiment, there is only one distance between the first position and the second position, that is, the device component to be selected is directly connected to the adjacent device component, then the first distance is 1; when the first position passes through N devices to reach the second position, the first distance is N+1, where N refers to any positive number greater than 0.

[0095] It should be noted that a first matrix is ​​formed according to the first distance between the first position and the second position, one dimension of the first matrix represents the device element to be selected, and the other dimension represents the adjacent device element, and the corresponding value in the matrix represents the first distance.

[0096] Step S1234: Obtain a second distance between the adjacent device element and the device element in the historical data, and form a second matrix according to the second distance, wherein the dimension of the second matrix is ​​equal to the dimension of the first matrix.

[0097] In this step, the second distance refers to the distance between the device element in the historical data and the adjacent device element. One dimension of the second matrix represents the device element in the historical data, and the other dimension represents the adjacent device element. The corresponding values ​​in the matrix represent the second distance, wherein the adjacent device elements of the second matrix are the same as the adjacent device elements of the first matrix at the same position. In an optional embodiment, the first matrix x = (x1, x2, x3), the second matrix y = (y1, y2, y3), then x1 and y1, x2 and y2, x3 and y3 represent the distance between the same adjacent device element and the device element to be selected or the device element in the historical data.

[0098] It should be noted that the dimension of the second matrix can be equal to the dimension of the first matrix through any dimension filling method of the device, for example, filling with 0 or filling with the average value of the existing data in the matrix to a position where the adjacent device elements are not close to the device elements in the historical data. In an optional embodiment, the first matrix x = (x1, x2, x3), the second matrix y = (y1, y2, y3), if x2 does not exist, then x2 = (x1+x3) / 2, to facilitate the subsequent steps of calculating the distance between the first matrix and the second matrix.

[0099] Step S1235: Obtain a third recommended value of the model of the device component according to the distance value between the first matrix and the second matrix.

[0100] In this step, the distance value between the first matrix and the second matrix can be calculated by any matrix distance calculation method in the related art, such as Manhattan distance, Euclidean distance, etc. The smaller the distance value between the first matrix and the second matrix, the more similar the device component to be selected is to the device component in the historical data, and the higher the third recommended value of the model of the device component in the historical data.

[0101] In this embodiment, through steps S1231 to S1235, the first position of the device element to be selected and the second position of the adjacent device element connected to the device element to be selected are obtained, and a first matrix is ​​formed according to the first distance between the first position and the second position; the second distance between the adjacent device element and the device element in the historical data is obtained, and a second matrix is ​​formed according to the second distance, and the dimension of the second matrix is ​​equal to the dimension of the first matrix; the third recommended value of the model of the device element is obtained according to the distance value between the first matrix and the second matrix. The solution of this embodiment can achieve the purpose of accurately obtaining the third recommended value according to the position information and improving the accuracy of the third recommended value.

[0102] In one embodiment, if Figure 7 As shown, step S1233 is further explained, which includes but is not limited to step S12331.

[0103] Step S12331: Setting a distance threshold for reducing the complexity of the first matrix, wherein the first distance is less than or equal to the distance threshold, and the second distance is less than or equal to the distance threshold.

[0104] In this step, the distance threshold is used to reduce the complexity of the first matrix. The first distance refers to the distance between the device element to be selected and the adjacent device element. When the first distance is less than or equal to the distance threshold, when the distance between the device element to be selected and the adjacent device element is greater than the distance threshold, the distance between the adjacent device element and the device element to be selected is not stored in the first matrix.

[0105] In this embodiment, through step S12331, a distance threshold is set to reduce the complexity of the first matrix, wherein the first distance is less than or equal to the distance threshold. Since in the drawing, there is a relationship between the device components and other components, when the drawing is too complex, the amount of calculation will increase. Therefore, setting the distance threshold can achieve the purpose of reducing the amount of calculation of the third recommendation.

[0106] In one embodiment, if Figure 8 As shown, step S1234 is further explained, which includes but is not limited to step S12341.

[0107] Step S12341: When the neighboring device component is not connected to the device component in the historical data, lower the third recommended value of the model of the device component in the historical data.

[0108] In this step, the adjacent device element refers to the device element adjacent to the device element to be selected. When the adjacent device element is not connected to the device element in the historical data, it means that the device element in the historical data must be different from the device element to be selected, thereby reducing the third recommended value of the model of the device element in the historical data.

[0109] In this embodiment, through step 12341, when the adjacent device component is not connected to the device component in the historical data, the third recommended value of the model of the device component in the historical data is reduced, thereby achieving the purpose of improving the rationality of the third recommended value.

[0110] In one embodiment, if Fig. 9 As shown, step S1234 is further explained, which includes but is not limited to step S910.

[0111] Step S910: When the second distance is greater than the distance threshold, lower the third recommended value of the model of the equipment component in the historical data.

[0112] In this step, the second distance refers to the distance between the neighboring device component and the device component in the historical data. When the second distance is greater than the distance threshold, the positional relationship between the device component in the historical data and the device component to be selected is inconsistent, and the third recommended value is reduced.

[0113] In this embodiment, through step S910, when the second distance is greater than the distance threshold, the third recommended value of the model of the equipment component in the historical data is reduced, so as to achieve the purpose of improving the rationality of the third recommended value.

[0114] In addition, an embodiment of the present invention further provides a controller, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0115] The processor and the memory may be connected via a bus or other means.

[0116] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0117] The non-transient software program and instructions required to implement the data processing method of the above embodiment are stored in the memory. When executed by the processor, the data processing method of the above embodiment is executed, for example, the above described Figure 1 Steps S110 to S140 of the method, Figure 2 Steps S121 to S124 of the method, Figure 3 Step S131 of the method, Figure 4Step S1211 of the method, Figure 5 Method step S1221, Figure 6 Steps S1231 to S11235 of the method, Figure 7 Method step S12331, Figure 8 Method steps S12341, Fig. 9 Method step S910 in .

[0118] In addition, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions. The computer-executable instructions are executed by a processor or a controller, for example, by a processor of the network device in the above embodiment, so that the above processor can execute the data processing method in the above embodiment, for example, execute the above described Figure 1 Steps S110 to S140 of the method, Figure 2 Steps S121 to S124 of the method, Figure 3 Step S131 of the method, Figure 4 Step S1211 of the method, Figure 5 Method step S1221, Figure 6 Steps S1231 to S11235 of the method, Figure 7 Method step S12331, Figure 8 Method steps S12341, Fig. 9 Method step S910 in .

[0119] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed methods above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium or a non-transitory medium and a communication medium or a temporary medium. As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules or other data. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk DVD or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0120] The embodiments of the present invention are described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Various changes can be made within the knowledge scope of ordinary technicians in the technical field without departing from the purpose of the present invention.

Claims

1. A method for recommending a model of a device component based on weighting, characterized in that: include: Obtain historical data of the distribution network; Obtaining a target recommended value for the model of the equipment component according to the historical data; Obtaining a target model of the device component according to the target recommendation value, wherein the target recommendation value of the target model is greater than the target recommendation value of the non-target model; Recommending the target model is to recommend the target model to the current drawing interface. During the selection process, the target model is recommended to the vicinity of the corresponding device component; The step of obtaining a target recommended value for the model of the device component according to the historical data includes: Acquire a first recommended value of the model of the device component, wherein the first recommended value includes: a recommended value obtained according to a price of the model of the device component; Obtaining the number of times a device component having the same model is used according to the historical data, and obtaining a second recommended value for the model of the device component according to the number of times used; Obtaining a first position of a device element to be selected, wherein the device element to be selected is a device element in the current drawing whose model has not yet been determined, and the position information of the device element to be selected is at least one of the following: position information of the device element in the drawing, specific coordinate information of the device element to be selected, and the position information is obtained through the position relationship or connection relationship between the device element and other elements; Acquire a second position of an adjacent equipment component connected to the equipment component to be selected; forming a first matrix according to a first distance between the first position and the second position; Acquire a second distance between the neighboring device element and the device element in the historical data, and form a second matrix according to the second distance, wherein the dimension of the second matrix is ​​equal to the dimension of the first matrix; Obtaining a third recommended value of the model of the device component according to the distance value between the first matrix and the second matrix; A target recommended value for the model of the device component is obtained according to the first recommended value, the second recommended value and the third recommended value.

2. The method for recommending a model of a device component based on weighting according to claim 1, characterized in that: Obtaining a target model according to the target recommendation value includes: The models of the equipment components in the historical data are sorted according to the target recommendation value to obtain the target model.

3. The method for recommending a model of a device component based on weighting according to claim 1, characterized in that: The first recommended value also includes: The recommended value is obtained based on the preset stability factor of the model of the equipment component.

4. The method for recommending a model of a device component based on weighting according to claim 1, characterized in that: The obtaining, according to the number of times used, a second recommended value of the model of the device component comprises: The second recommendation value is obtained by multiplying the number of times of use by a preset weight of the number of times of use.

5. The method for recommending a model of a device component based on weighting according to claim 1, characterized in that: The method of obtaining a third recommended value of the model of the device component according to the distance value between the first matrix and the second matrix further includes: A distance threshold is set for reducing the complexity of the first matrix, wherein the first distance is less than or equal to the distance threshold.

6. The method for recommending a model of a device component based on weighting according to claim 1, characterized in that: The obtaining of a second distance between the adjacent device element and the device element in the historical data includes: When the neighboring device component is not connected to the device component in the historical data, the third recommended value of the model of the device component in the historical data is lowered.

7. The method for recommending a model of a device component based on weighting according to claim 5, characterized in that: The obtaining of a second distance between the adjacent device element and the device element in the historical data includes: When the second distance is greater than the distance threshold, a third recommended value of the model of the equipment component in the historical data is reduced.

8. A controller, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for recommending a model of a device component based on weighting as claimed in any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method for recommending a model of a device component based on weighting according to any one of claims 1 to 7.

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