A digital twin model construction method, device and system for complex scenarios

Abstract

The present invention discloses a method, device and system for constructing a digital twin model in a complex scene, and relates to the technical field of electronic digital data processing. The method for constructing a digital twin model in a complex scene includes: obtaining layout evaluation parameters corresponding to a target exhibition hall, the layout evaluation parameters include a plurality of historical exhibit layout schemes and user browsing information under the historical exhibit layout schemes, and the user browsing information includes the user browsing booth, the user entering the booth time and the user leaving the booth time; based on the layout evaluation parameters, constructing a layout evaluation function of the target exhibition hall, the layout evaluation function is used to evaluate the exhibit layout effects of various exhibit layout schemes; according to the layout evaluation function, determining the target exhibit layout scheme with the best exhibit layout effect; based on the target exhibit layout scheme, constructing a digital twin model. The method for constructing a digital twin model in a complex scene provided by the present invention can improve the accuracy of the target layout scheme finally determined.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular, to a method, device, and system for constructing a digital twin model in a complex scenario. Background Art

[0002] For various digital exhibition halls, science and technology museums, and museums that need to continuously change the intelligent exhibition layout according to the changes of visitors, constructing a digital twin model is very important. By using the digital twin model to help optimize the exhibition layout, the visitor experience and exhibition effect can be improved.

[0003] In the existing methods, a target layout plan is selected from multiple exhibition layout plans, and finally a digital twin model is constructed according to the target layout plan to display the exhibits.

[0004] However, in the existing methods, a general layout plan selection method is used to determine the target layout plan, which does not consider the uniqueness of the exhibition objectives and constraints in the exhibition situation, resulting in poor accuracy of the finally determined target layout plan. Summary of the Invention

[0005] An embodiment of the present invention provides a method for constructing a digital twin model in a complex scenario, which can improve the accuracy of the finally determined target layout plan.

[0006] On the one hand, an embodiment of the present invention provides a method for constructing a digital twin model in a complex scenario, including:

[0007] Obtain layout evaluation parameters corresponding to the target exhibition hall, where the layout evaluation parameters include a variety of historical exhibition layout plans and user browsing information under the historical exhibition layout plans, and the user browsing information includes the user's browsing booth, the time when the user enters the booth, and the time when the user leaves the booth;

[0008] Based on the layout evaluation parameters, construct a layout evaluation function for the target exhibition hall, and the layout evaluation function is used to evaluate the exhibition layout effect of various exhibition layout plans;

[0009] According to the layout evaluation function, determine the target exhibition layout plan with the best exhibition layout effect;

[0010] Based on the target exhibition layout plan, construct a digital twin model.

[0011] On the one hand, an embodiment of the present invention provides a system for constructing a digital twin model in a complex scenario, including:

[0012] A parameter acquisition module, configured to acquire layout evaluation parameters corresponding to a target exhibition hall. The layout evaluation parameters include multiple historical exhibit layout schemes and user browsing information under the historical exhibit layout schemes. The user browsing information includes the booths browsed by the user, the time when the user enters the booth, and the time when the user leaves the booth.

[0013] A function construction module, configured to construct a layout evaluation function of the target exhibition hall based on the layout evaluation parameters. The layout evaluation function is used to evaluate the exhibit layout effects of various exhibit layout schemes.

[0014] A scheme determination module, configured to determine a target exhibit layout scheme with the optimal exhibit layout effect according to the layout evaluation function.

[0015] A model construction module, configured to construct a digital twin model based on the target exhibit layout scheme.

[0016] On the one hand, an embodiment of the present invention provides a digital twin model construction device in a complex scenario. The device includes: a memory and a program or instruction stored on the memory and executable on a processor. When the program or instruction is executed by the processor, it implements the digital twin model construction method in any aspect provided by the above embodiment of the present invention.

[0017] In the digital twin model construction method provided by the embodiment of the present invention, considering the uniqueness of the constraint conditions in the exhibition situation, the historical exhibit layout scheme corresponding to the target exhibition hall and the user browsing information under the historical exhibit layout scheme are acquired. At the same time, considering the uniqueness of the exhibition objectives in the exhibition situation, a layout evaluation function for evaluating the exhibit layout effects of the target exhibition hall under various exhibit layout schemes is constructed according to the historical exhibit layout scheme corresponding to the target exhibition hall and the user browsing information under the historical exhibit layout scheme. Finally, a digital twin model is constructed by selecting a target exhibit layout scheme with the optimal exhibit layout effect according to the layout evaluation function. In this way, by comprehensively considering the uniqueness of the exhibition objectives and constraint conditions in the exhibition situation, the present invention constructs a layout evaluation function, which can accurately evaluate the actual exhibit layout effects of various exhibit layouts, ensure that the algorithm gives priority to considering those layouts that best meet the needs of the exhibition hall during the evolution process, and thus improve the accuracy of the finally determined target layout scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 Schematic flowchart of the first method for constructing a digital twin model in a complex scenario provided by an embodiment of the present invention;

[0020] Figure 2 Schematic diagram of a digital twin model provided by an embodiment of the present invention;

[0021] Figure 3 Schematic flowchart of the second method for constructing a digital twin model in a complex scenario provided by an embodiment of the present invention;

[0022] Figure 4 Schematic flowchart of the third method for constructing a digital twin model in a complex scenario provided by an embodiment of the present invention;

[0023] Figure 5 Schematic diagram of the structure of a digital twin model construction system in a complex scenario provided by an embodiment of the present invention;

[0024] Figure 6 Schematic diagram of the structure of a digital twin model construction device in a complex scenario provided by an embodiment of the present invention. Detailed implementation manners

[0025] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of a method, device, and system for constructing a digital twin model in a complex scenario according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments may be combined in any suitable form.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0027] It should be noted that the acquisition, storage, use, processing, etc. of data in the technical solution of the present invention all comply with the relevant regulations of national laws and regulations.

[0028] It should be noted that in the embodiments of the present invention, some existing industry solutions such as certain software, components, models, etc. may be mentioned. They should be regarded as exemplary, and their purpose is only to illustrate the feasibility in the implementation of the technical solution of the present invention, but it does not mean that the applicant has already or necessarily used this solution.

[0029] In the existing methods, a target layout plan is selected from multiple exhibit layout plans, and finally a digital twin model is constructed according to the target layout plan for exhibit display. However, in the existing methods, a general layout plan selection method is used to determine the target layout plan, which does not take into account the uniqueness of the exhibition objectives and constraints in the exhibition situation, resulting in poor accuracy of the finally determined target layout plan.

[0030] The object of the present invention is to provide a method, device and system for constructing a digital twin model in a complex scenario. In the method for constructing a digital twin model in a complex scenario provided by the embodiments of the present invention, considering the uniqueness of the constraints in the exhibition situation, the historical exhibit layout plan corresponding to the target exhibition hall and the user browsing information under the historical exhibit layout plan are obtained. At the same time, considering the uniqueness of the exhibition objectives in the exhibition situation, a layout evaluation function for evaluating the exhibit layout effect of the target exhibition hall under various exhibit layout plans is constructed according to the historical exhibit layout plan corresponding to the target exhibition hall and the user browsing information under the historical exhibit layout plan. Finally, a digital twin model is constructed by selecting the target exhibit layout plan with the best exhibit layout effect according to the layout evaluation function. In this way, by comprehensively considering the uniqueness of the exhibition objectives and constraints in the exhibition situation and constructing a layout evaluation function, the present invention can accurately evaluate the actual exhibit layout effect of various exhibit layouts, ensure that the algorithm gives priority to considering those layouts that best meet the needs of the exhibition hall during the evolution process, and thus improve the accuracy of the finally determined target layout plan.

[0031] The following introduces the specific embodiments of a method, device and system for constructing a digital twin model in a complex scenario provided by the embodiments of the present invention.

[0032] First, the method for constructing a digital twin model in a complex scenario provided by the embodiments of the present invention is introduced below.

[0033] Figure 1 A flowchart of a method for constructing a digital twin model in a complex scenario is provided. The method for constructing a digital twin model in a complex scenario can be applied to a server, and the method for constructing a digital twin model in a complex scenario may include the following S101 to S104.

[0034] S101, obtain the layout evaluation parameters corresponding to the target exhibition hall. The layout evaluation parameters include a variety of historical exhibit layout plans and the user browsing information under the historical exhibit layout plans. The user browsing information includes the user browsing booth, the time when the user enters the booth, and the time when the user leaves the booth.

[0035] In this embodiment, the historical exhibition layout plan is used to represent the layout information between exhibits and their corresponding exhibition booths during a historical time period. By way of example, the exhibition booths may include five booths {1, 2, 3, 4, 5}, the exhibits may include five exhibits {A, B, C, D, E}, and the historical exhibition layout plan may be {1-B, 2-D, 3-E, 4-A, 5-C}.

[0036] The historical exhibition layout plan may be the actual exhibition layout plan adopted by the target exhibition hall in the historical stage, or the simulated exhibition layout plan adopted by the target exhibition hall in the historical stage. By way of example, with one hour as the preset interval duration, an exhibition layout plan is randomly generated every hour, and simulation is performed on this exhibition layout plan.

[0037] As an example, the server may obtain all the historical exhibition layout plans corresponding to the target exhibition hall and the user browsing information of each browsing user under each historical exhibition layout plan within a preset past time period (such as the past week) from the database. Specifically, the server may pre-collect the user browsing information of each browsing user under each historical exhibition layout plan through devices such as cameras and infrared sensors, including the user's browsing booth, the time when the user enters the booth, and the time when the user leaves the booth, etc.

[0038] S102. Based on the layout evaluation parameters, construct a layout evaluation function for the target exhibition hall. The layout evaluation function is used to evaluate the exhibition layout effects of various exhibition layout plans.

[0039] In this embodiment, the layout evaluation function is used to represent the matching relationship between the exhibition layout plan and the corresponding exhibition layout effect.

[0040] As an example, the server may pre-define multiple evaluation indicators. Then, according to the layout evaluation parameters, determine the evaluation scores corresponding to each evaluation indicator. Assign different weights to different evaluation scores, and obtain the exhibition layout effect corresponding to each historical exhibition layout plan through weighted summation. Finally, perform function fitting based on the exhibition layout effect corresponding to each historical exhibition layout plan to obtain the layout evaluation function of the target exhibition hall.

[0041] For example, the evaluation indicators may include traffic distribution uniformity, browsing depth, and path efficiency. Among them, traffic distribution uniformity is used to evaluate the difference in the number of people flow between booths, and is determined according to the user's browsing booth of each browsing user under each historical exhibition layout plan. Browsing depth is used to evaluate the average time that browsing users stay in each booth, reflecting the attraction of the exhibits, and is determined according to the time when the user enters the booth and the time when the user leaves the booth of each browsing user under each historical exhibition layout plan.

[0042] S103. Determine the target exhibit layout plan with the optimal exhibit layout effect according to the layout evaluation function.

[0043] In this embodiment, the server first determines the historical exhibit layout plan with the optimal exhibit layout effect according to the layout evaluation function as the candidate layout plan. Then, it further verifies the feasibility of the candidate layout plan through simulation tests (such as using VR (Virtual Reality) technology to simulate visitor behavior), and fine-tunes the candidate layout plan according to the results of the simulation tests to obtain the final target exhibit layout plan.

[0044] S104. Build a digital twin model based on the target exhibit layout plan.

[0045] In this embodiment, as Figure 2 shown, a schematic diagram of a digital twin model is provided. Specifically, the server first uses 3D (3Dimensions) modeling software to create a 3D model of the target exhibition hall and numbers and sorts each booth in the target exhibition hall. And it integrates all digital exhibits to create 3D models of each exhibit, and also numbers and sorts all digital exhibits.

[0046] Finally, according to the target exhibit layout plan, map and associate each exhibit with the corresponding booth to build the final digital twin model.

[0047] In the method for building a digital twin model in a complex scenario provided in this embodiment, considering the uniqueness of the constraint conditions in the exhibition situation, the historical exhibit layout plan corresponding to the target exhibition hall and the user browsing information under the historical exhibit layout plan are obtained. At the same time, comprehensively considering the uniqueness of the exhibition objectives in the exhibition situation, a layout evaluation function for evaluating the exhibit layout effect of the target exhibition hall under various exhibit layout plans is constructed according to the historical exhibit layout plan corresponding to the target exhibition hall and the user browsing information under the historical exhibit layout plan. Finally, a digital twin model is built by selecting the target exhibit layout plan with the optimal exhibit layout effect according to the layout evaluation function. In this way, by comprehensively considering the uniqueness of the exhibition objectives and constraint conditions in the exhibition situation, the present invention constructs a layout evaluation function, which can accurately evaluate the actual exhibit layout effect of various exhibit layouts, ensure that the algorithm gives priority to considering those layouts that best meet the needs of the exhibition hall during the evolution process, and thus improve the accuracy of the finally determined target layout plan.

[0048] As an alternative embodiment, S101 may specifically include:

[0049] Divide the target exhibition hall according to the booth distribution information to obtain a plurality of exhibition hall areas, and each exhibition hall area corresponds to a booth;

[0050] Obtain multiple historical exhibit layout plans, each historical exhibit layout plan corresponding to a historical time period, and the duration of each historical time period matching the preset interval duration;

[0051] Track the browsing users in the target exhibition hall to obtain the user browsing booths, the user entry time into the booths, and the user exit time from the booths corresponding to each historical exhibit layout plan.

[0052] In this embodiment, the preset interval duration is used to represent the layout duration corresponding to the exhibit layout plan. By way of example, the preset interval duration is one hour, that is, a new exhibit layout plan is switched every hour in the historical stage.

[0053] As an example, the server first obtains the detailed booth distribution map of the target exhibition hall, and then divides the target exhibition hall into multiple logically independent exhibition hall areas according to the detailed booth distribution map. Each exhibition hall area corresponds to a booth, and at the same time, a unique identification information is assigned to each exhibition hall area.

[0054] Then, the server obtains all the historical exhibit layout plans corresponding to the target exhibition hall within a preset past time period (such as the past week) from the database. And during the implementation display period or the simulated display period of each historical exhibit layout plan, through devices such as Bluetooth beacons or cameras, according to the identification information corresponding to each exhibition hall area, the movement trajectory of the visitors is tracked, so as to obtain the user browsing booths, the user entry time into the booths, and the user exit time from the booths corresponding to each historical exhibit layout plan.

[0055] Through this embodiment, the target exhibition hall is divided into multiple exhibition hall areas according to the booth distribution information, and then the browsing users in the target exhibition hall are tracked, and the layout evaluation parameters corresponding to the target exhibition hall can be obtained. In this way, through tracking the browsing users, this embodiment accurately obtains the user browsing booths, the user entry time into the booths, and the user exit time from the booths, which helps to construct a layout evaluation function based on the layout evaluation parameters subsequently and improve the accuracy of the finally determined target layout plan.

[0056] As an alternative embodiment, as Figure 3 shown, S102 may specifically include the following S301 - S304:

[0057] S301, determine the attention degree of each booth in the target exhibition hall according to the user browsing information under each historical exhibit layout plan;

[0058] S302, determine the first priority of each exhibit in the target exhibition hall according to the attention degree of each booth in the target exhibition hall, each historical exhibit layout plan, and the user browsing information under each historical exhibit layout plan;

[0059] S303, determining the optimality of each exhibit according to the first priority of each exhibit in the target exhibition hall, where the optimality is used to characterize the exhibition gain that the exhibit can bring;

[0060] S304, based on the attention of each booth in the target exhibition hall and the optimality of each exhibit, construct a layout evaluation function of the target exhibition hall.

[0061] In this embodiment, the attention of the booth is used to represent the degree to which the booth is easily noticed by browsing users. The higher the attention, the higher the attraction of the booth in the entire exhibition layout.

[0062] The first priority of an exhibit is used to indicate the degree to which the exhibit is favored by browsing users. The higher the first priority, the more visitors the exhibit can attract.

[0063] As an example, the server determines the time each browsing user stays in front of each booth based on the user browsing information, and then calculates the average time each booth is visited, which is used as the attention level of each booth.

[0064] Then, the server determines the average visitor flow of each exhibit based on the historical exhibit layout plans and the user browsing information under each historical exhibit layout plan. At the same time, the corresponding adjustment weight is set based on the influence of each booth's attention, and the average visitor flow of each exhibit is adjusted to obtain the first priority of each exhibit.

[0065] At the same time, optimality can not only consider the attractiveness of the exhibits themselves, but also how they contribute to the viewing and educational value of the entire exhibition. Therefore, the server scores each exhibit based on its historical importance, artistic value, scientific significance, and first priority, and obtains the optimality corresponding to each exhibit.

[0066] Finally, the server designs a set of comprehensive evaluation indicators, using weighted summation, fuzzy evaluation, multi-objective optimization and other methods to integrate the booth's attention and the optimality of the exhibits into one function, thereby obtaining the layout evaluation function of the target exhibition hall.

[0067] Through this embodiment, the layout evaluation function of the target exhibition hall is constructed by using the attention of each booth in the target exhibition hall and the optimality of each exhibit. The layout evaluation function is constructed from multiple factors, which can accurately evaluate the actual layout effects of various exhibit layouts, thereby improving the accuracy of the final target layout plan.

[0068] As an optional embodiment, S301 may specifically include:

[0069] ​Based on the user browsing information under each historical exhibition layout plan, determine the number of first browsing users of the target booth and the target browsing time of each first browsing user, where the target booth is any one of the booths in the target exhibition hall;

[0070] Determine the attention level of the target booth according to the number of first browsing users and the target browsing time of each first browsing user.

[0071] In this embodiment, the number of first browsing users is used to represent the total number of users who have browsed the target booth, the first browsing user is used to represent the browsing user who has browsed the target booth, and the target browsing time is used to represent the time when the first browsing user enters the target booth.

[0072] The attention level of the target booth can be specifically determined by the following formula 1:

[0073] Formula 1

[0074] In the formula, represents the attention level of booth Q, exp represents the exponential function with the natural constant e as the base, n represents the number of first browsing users of booth Q, represents the target browsing time of the i-th first browsing user, represents the time when the i-th first browsing user enters the target exhibition hall, represents the sum from the 1st to the nth.

[0075] Specifically, when the historical exhibition layout plan is the exhibition layout plan actually adopted by the target exhibition hall in the historical stage, the time when the first browsing user enters the target exhibition hall is determined by tracking devices such as cameras and Bluetooth beacons; when the historical exhibition layout plan is the exhibition layout plan simulated by the target exhibition hall in the historical stage, the start simulation time is determined as the time when the first browsing user enters the target exhibition hall.

[0076] Among them, represents the time difference between the first browsing user entering the target exhibition hall and entering the target booth. The smaller the time difference, the closer the target booth is to the entrance of the target exhibition hall, and the more likely the target booth is to attract the attention of the audience, so the higher the attention level of the target booth.

[0077] The attention level of booth Q The higher it is, the higher the probability that the browsing user passes by booth Q, that is, booth Q has higher attractiveness in the entire exhibition layout.

[0078] Through this embodiment, based on the number of first browsing users of the target exhibition booth and the target browsing times of each first browsing user, the attention degree of the target exhibition booth can be accurately determined. Thereby, it is helpful to subsequently accurately construct the layout evaluation function of the target exhibition hall by using the attention degree of the exhibition booth, and the actual exhibition layout effect of various exhibit layouts can be accurately evaluated, thereby improving the accuracy of the finally determined target layout plan.

[0079] As an alternative embodiment, as Figure 4 shown, S302 may specifically include the following S401 - S403:

[0080] S401, using each historical exhibit layout plan, generate a booth change sequence of the target exhibit, where the target exhibit is any one of the exhibits in the target exhibition hall, and the booth change sequence is used to characterize the historical booths corresponding to the target exhibit under each historical exhibit layout plan;

[0081] S402, based on the booth change sequence and the user browsing information under each historical exhibit layout plan, determine the number of second browsing users corresponding to the target exhibit at each historical booth and the target browsing duration of each second browsing user;

[0082] S403, based on the number of booths in the booth change sequence, the attention degree of each historical booth in the booth change sequence, the number of second browsing users, and the target browsing duration, determine the first priority of the target exhibit.

[0083] In this embodiment, the booth change sequence is used to characterize the change situation of the historical booths corresponding to the target exhibit. By way of example, the booth change sequence of the target exhibit may be {1, 4, 3, 5, 4}, indicating that the target exhibit is first at booth 1, then becomes booth 4, then becomes booth 3, then becomes booth 5, and finally becomes booth 4 again.

[0084] The second browsing user is used to characterize the browsing users who have browsed the target exhibit under each historical exhibit layout plan.

[0085] The number of second browsing users is used to characterize the number of people who have browsed the target exhibit under each historical exhibit layout plan, and the target browsing duration is used to characterize the total browsing duration of the second browsing users for the target exhibit.

[0086] As an example, the server finds the historical booths corresponding to the target exhibit in each historical exhibit layout plan according to each historical exhibit layout plan, and generates a booth change sequence of the target exhibit in the time sequence corresponding to each historical exhibit layout plan.

[0087] Then, based on the booth change sequence and the user browsing information under each historical exhibit layout plan, count the number of second browsing users corresponding to the target exhibit at each historical booth and the target browsing duration of each second browsing user.

[0088] Finally, an evaluation model is constructed using a statistical or machine learning model, with the number of exhibition booths, the attention of each historical booth, the number of second-view users, and the target browsing duration as input variables, and the first priority of the target exhibit as the output variable, so as to obtain the first priority of the target exhibit according to the evaluation model.

[0089] As another example, the first priority of the target exhibit can be specifically determined by the following formula 2:

[0090] Formula 2

[0091] In the formula, represents the first priority of exhibit A, V represents the number of exhibition booths corresponding to exhibit A, represents the attention of the historical booth corresponding to exhibit A at the i-th historical booth, w represents the number of second-view users corresponding to exhibit A at the i-th historical booth, represents the target browsing duration of the j-th second-view user of exhibit A at the i-th historical booth, represents the summation from the 1st to the v-th.

[0092] Among them, represents the average browsing duration corresponding to exhibit A at the i-th historical booth. The longer the average browsing duration, the more attractive it is to browsing users, that is, the higher the first priority of the exhibit. When the attention of the historical booth is relatively low, but still can attract browsing users to stay for a relatively long time on average, it indicates that the exhibit performs outstandingly in attracting audiences. That is, the lower the attention of the historical booth, the higher the first priority of the exhibit.

[0093] The first priority of exhibit A The higher it is, the higher the probability that browsing users will stay after passing by exhibit A, that is, exhibit A has higher attractiveness in the entire exhibition layout.

[0094] Through this embodiment, according to the number of exhibition booths corresponding to the target exhibit, the attention of each historical booth, the number of second-view users, and the target browsing duration, the first priority of the target exhibit can be accurately determined. This helps to subsequently accurately construct the layout evaluation function of the target exhibition hall using the first priority of the exhibit, and can accurately evaluate the actual exhibit layout effect of various exhibit layouts, thereby improving the accuracy of the finally determined target layout plan.

[0095] As an optional embodiment, after S403, the method for constructing the digital twin model in this complex scenario may specifically further include:

[0096] Based on the booth change sequence of the target exhibit, obtain the second priority of the target historical exhibit corresponding to each historical booth of the target exhibit, where the target historical exhibit is the exhibit that was in the historical booth before the target exhibit;

[0097] Determine the third priority of the target exhibit according to the first priority of the target exhibit and the second priorities corresponding to the target exhibit;

[0098] S303 may specifically include:

[0099] Determine the optimality of each exhibit according to the third priority of each exhibit in the target exhibition hall.

[0100] In this embodiment, the second priority is the priority of the target historical exhibit that was in the historical booth before the target exhibit, and the third priority is the weighted priority obtained after correcting the first priority.

[0101] As an example, the third priority of the target exhibit can be specifically determined by the following formula 3:

[0102] Formula 3

[0103] In the formula, represents the third priority of exhibit A, exp represents the exponential function with the natural constant e as the base, represents the sum from the 1st to the vth, where v represents the number of booths corresponding to exhibit A, represents the second priority of the target historical exhibit corresponding to exhibit A at the i-th historical booth, represents the first priority of exhibit A.

[0104] Among them, in the case where an exhibit is in multiple booths as the layout changes, if the previous exhibit at this booth is less concerned, it proves that it is more likely to be attracted by this exhibit at this time, and the priority of this exhibit should be higher. That is, the lower the second priority of the target historical exhibit, the higher the third priority of the target exhibit.

[0105] Through this embodiment, the first priority of the target exhibit is corrected according to the second priorities of the target historical exhibits corresponding to the target exhibit, so as to obtain the third priority of the target exhibit. In this way, the rationality of the priority of the target exhibit can be improved, which helps to accurately construct the layout evaluation function of the target exhibition hall by using the third priority of the exhibits subsequently, and can accurately evaluate the actual layout effect of various exhibit layouts, thereby improving the accuracy of the finally determined target layout plan.

[0106] As an alternative embodiment, determining the optimality of each exhibit according to the third priority of each exhibit in the target exhibition hall may specifically include:

[0107] Obtain the current exhibition booth corresponding to the target exhibit under the current exhibit layout plan;

[0108] Track the browsing users in the target exhibition hall to obtain the current number of browsing people at the current exhibition booth;

[0109] Filter the current number of browsing people according to the user browsing information of the target exhibit under each historical exhibit layout plan to obtain the number of non-first-time browsing people;

[0110] Determine the optimality of the target exhibit according to the number of non-first-time browsing people, the current number of browsing people, and the third priority of the target exhibit.

[0111] In this embodiment, the optimality of the target exhibit can be specifically determined by the following formula 4:

[0112] Formula 4

[0113] In the formula, represents the optimality corresponding to the target exhibit A at the current exhibition booth k, represents the current number of browsing people at the current exhibition booth k, represents the number of non-first-time browsing people of the target exhibit A at the current exhibition booth k, represents the third priority of the target exhibit A at the current exhibition booth k.

[0114] Among them, represents the number of first-time browsing people of the target exhibit A at the current exhibition booth k. The more the number of first-time browsing people, the more people are attracted, that is, the greater the optimality of the target exhibit.

[0115] The optimality corresponding to the target exhibit A at the current exhibition booth k The greater it is, the higher the gain that can be brought by placing the target exhibit A at the current exhibition booth k.

[0116] Through this embodiment, according to the number of non-first-time browsing people, the current number of browsing people, and the third priority of the target exhibit, the optimality of the target exhibit can be accurately determined. Thus, it helps to accurately construct the layout evaluation function of the target exhibition hall by using the optimality of the exhibit later, and can accurately evaluate the actual exhibit layout effect of various exhibit layouts, thereby improving the accuracy of the finally determined target layout plan.

[0117] As an alternative embodiment, S304 may specifically include:

[0118] Determine the layout evaluation function of the target exhibition hall through the following formula 5:

[0119] Formula 5

[0120] Wherein, S represents the layout evaluation function of the target exhibition hall, m represents the total number of exhibition booths in the target exhibition hall, f represents the maximum-minimum normalization function, represents the attention degree of the i-th exhibition booth in the target exhibition hall, represents the optimality of the exhibits on the i-th exhibition booth in the exhibit layout plan, represents the summation from the 1st to the m-th.

[0121] Among them, it means that the smaller the attention degree of the i-th exhibition booth, the greater the optimality of the exhibits on the i-th exhibition booth, and the greater the result of the layout evaluation function of the target exhibition hall. Specifically, by placing high-priority exhibits in positions with lower attention degrees, it is possible to avoid excessive concentration of resources in popular areas, so that the space of the entire exhibition area can be used more evenly, that is, the exhibit layout effect of the exhibit layout plan is better.

[0122] Through this embodiment, according to the attention degrees of each exhibition booth in the target exhibition hall and the optimality of each exhibit, the layout evaluation function of the target exhibition hall is accurately constructed, and the actual exhibit layout effect of various exhibit layout plans can be accurately evaluated, thereby improving the accuracy of the finally determined target layout plan.

[0123] As an alternative embodiment, S103 may specifically include:

[0124] Randomly generate multiple initial exhibit layout plans;

[0125] According to the layout evaluation function, determine the fitness corresponding to each initial exhibit layout plan;

[0126] Based on the fitness corresponding to each initial exhibit layout plan, screen each initial exhibit layout plan to obtain the top N candidate exhibit layout plans with the highest fitness, where N is a positive integer;

[0127] According to each candidate exhibit layout plan, perform plan adjustment in a loop until a preset stop condition is reached, and obtain the target exhibit layout plan with the best exhibit layout effect.

[0128] In this embodiment, the fitness is the result of the layout evaluation function, which is used to reflect the exhibit layout effect corresponding to the exhibit layout plan.

[0129] The preset stop condition is used to represent the condition for stopping the adjustment of the exhibit layout plan. By way of example, the preset stop condition may be that the number of adjustments reaches a threshold number.

[0130] As an example, the server first randomly generates M initial exhibit layout plans. Then, according to the layout evaluation function, determine the fitness corresponding to each initial exhibit layout plan. Then, adopt the elite selection method to select 10% of the initial exhibit layout plans with the highest fitness as candidate exhibit layout plans.

[0131] Then, the genetic algorithm is adopted to combine the features of two candidate exhibition layout schemes through single-point crossover operation to generate a new exhibition layout scheme. Specifically, taking two candidate exhibition layout schemes as the "parent generations", a position is randomly selected in the gene sequences of the parent generations. Suppose there are Parent Generation 1 and Parent Generation 2. Before the crossover point: copy the first half of Parent Generation 1 (from the beginning to the crossover point) to Offspring 1. After the crossover point: copy the second half of the layout of Parent Generation 2 (from the crossover point to the end) to Offspring 1.

[0132] Perform the same operation on Offspring 2, but swap the roles of the parent generations, that is, combine the first half of Parent Generation 2 and the second half of Parent Generation 1 to form Offspring 2, thus generating two new exhibition layout schemes.

[0133] Meanwhile, a mutation rate of 1% is set for the newly generated exhibition layout schemes for random mutation (that is, randomly swap and adjust the positions of the exhibits in the exhibition layout scheme) to explore more possible layout combinations. Then, according to the layout evaluation function, the fitness corresponding to each new exhibition layout scheme is determined.

[0134] By repeatedly executing the adjustment operation of the exhibition layout scheme until the fitness improvement does not exceed 1%, the exhibition layout scheme corresponding to the best fitness is determined as the target exhibition layout scheme.

[0135] Through this embodiment, multiple initial exhibition layout schemes are randomly generated first, and then the fitness corresponding to each initial exhibition layout scheme is calculated to determine the corresponding candidate exhibition layout schemes. Finally, the candidate exhibition layout schemes are adjusted according to the fitness, so as to obtain the target exhibition layout scheme with the optimal exhibition layout effect. In this way, by using the layout evaluation function to accurately evaluate the actual exhibition layout effect of various exhibition layouts, the accuracy of the finally determined target layout scheme can be improved.

[0136] A method for constructing a digital twin model under complex scenarios. Correspondingly, the present invention also provides a specific embodiment of a system for constructing a digital twin model under complex scenarios.

[0137] Figure 5 Fig. shows the structural schematic diagram of the system for constructing a digital twin model under complex scenarios provided by the embodiment of the present invention. The system 500 for constructing a digital twin model under complex scenarios may include a parameter acquisition module 510, a function construction module 520, a scheme determination module 530, and a model construction module 540.

[0138] A parameter acquisition module 510 is configured to acquire layout evaluation parameters corresponding to a target exhibition hall. The layout evaluation parameters include a variety of historical exhibit layout schemes and user browsing information under the historical exhibit layout schemes. The user browsing information includes the booths browsed by the user, the time when the user enters the booth, and the time when the user leaves the booth.

[0139] A function construction module 520 is configured to construct a layout evaluation function of the target exhibition hall based on the layout evaluation parameters. The layout evaluation function is used to evaluate the exhibit layout effects of various exhibit layout schemes.

[0140] A scheme determination module 530 is configured to determine a target exhibit layout scheme with the optimal exhibit layout effect according to the layout evaluation function.

[0141] A model construction module 540 is configured to construct a digital twin model based on the target exhibit layout scheme.

[0142] As an optional embodiment, the parameter acquisition module 510 specifically includes the following units:

[0143] An exhibition hall division unit is configured to divide the target exhibition hall according to the booth distribution information to obtain a plurality of exhibition hall areas, and each exhibition hall area corresponds to a booth.

[0144] A scheme acquisition unit is configured to acquire a variety of historical exhibit layout schemes. Each historical exhibit layout scheme corresponds to a historical time period, and the duration of each historical time period matches the preset interval duration.

[0145] A user tracking unit is configured to track the browsing users in the target exhibition hall to obtain the booths browsed by the browsing users, the time when the users enter the booth, and the time when the users leave the booth corresponding to each historical exhibit layout scheme.

[0146] As an optional embodiment, the function construction module 520 specifically includes the following units:

[0147] An attention degree determination unit is configured to determine the attention degree of each booth in the target exhibition hall according to the user browsing information under each historical exhibit layout scheme.

[0148] A priority determination unit is configured to determine the first priority of each exhibit in the target exhibition hall according to the attention degree of each booth in the target exhibition hall, each historical exhibit layout scheme, and the user browsing information under each historical exhibit layout scheme.

[0149] An optimality determination unit is configured to determine the optimality of each exhibit according to the first priority of each exhibit in the target exhibition hall. The optimality is used to characterize the exhibition gain that the exhibit can bring.

[0150] A function construction unit, configured to construct a layout evaluation function of the target exhibition hall based on the attention degrees of each booth in the target exhibition hall and the optimality of each exhibit.

[0151] As an optional embodiment, the attention degree determination unit specifically includes the following sub-units:

[0152] The first information determination sub-unit is configured to determine the number of first browsing users of the target booth and the target browsing time of each first browsing user based on the user browsing information under each historical exhibit layout plan, where the target booth is any one of the booths in the target exhibition hall;

[0153] The attention degree determination sub-unit is configured to determine the attention degree of the target booth according to the number of first browsing users and the target browsing time of each first browsing user.

[0154] As an optional embodiment, the priority determination unit specifically includes the following sub-units:

[0155] The sequence generation sub-unit is configured to generate a booth change sequence of the target exhibit by using each historical exhibit layout plan, where the target exhibit is any one of the exhibits in the target exhibition hall, and the booth change sequence is used to represent the historical booth corresponding to the target exhibit under each historical exhibit layout plan;

[0156] The second information determination sub-unit is configured to determine the number of second browsing users corresponding to the target exhibit at each historical booth and the target browsing duration of each second browsing user according to the booth change sequence and the user browsing information under each historical exhibit layout plan;

[0157] The priority determination sub-unit is configured to determine the first priority of the target exhibit according to the number of booths in the booth change sequence, the attention degrees of each historical booth in the booth change sequence, the number of second browsing users, and the target browsing duration.

[0158] As an optional embodiment, the priority determination unit further includes the following sub-units:

[0159] The priority acquisition sub-unit is configured to obtain the second priority of the historical exhibit under each historical booth corresponding to the target exhibit based on the booth change sequence of the target exhibit, where the historical exhibit is the exhibit located in the previous historical booth before the target exhibit;

[0160] The priority determination sub-unit is further configured to determine the third priority of the target exhibit according to the first priority of the target exhibit and the second priorities corresponding to the target exhibit.

[0161] The optimality determination unit is specifically configured to:

[0162] Determine the optimality of each exhibit according to the third priority of each exhibit in the target exhibition hall.

[0163] As an alternative embodiment, the optimality determination unit specifically includes the following sub-units:

[0164] The booth acquisition sub-unit is used to acquire the current booth corresponding to the target exhibit under the current exhibit layout plan;

[0165] The number determination sub-unit is used to track the browsing users in the target exhibition hall to obtain the current number of browsers at the current booth;

[0166] The number screening sub-unit is used to screen the current number of browsers according to the user browsing information of the target exhibit under each historical exhibit layout plan to obtain the number of non-first-time browsers;

[0167] The optimality determination sub-unit is used to determine the optimality of the target exhibit according to the number of non-first-time browsers, the current number of browsers, and the third priority of the target exhibit.

[0168] As an alternative embodiment, the scheme determination module 530 specifically includes the following units:

[0169] The scheme generation unit is used to randomly generate multiple initial exhibit layout plans;

[0170] The fitness determination unit is used to determine the fitness corresponding to each initial exhibit layout plan according to the layout evaluation function;

[0171] The scheme screening unit is used to screen each initial exhibit layout plan based on the fitness corresponding to each initial exhibit layout plan to obtain the top N candidate exhibit layout plans with the highest fitness, where N is a positive integer;

[0172] The scheme adjustment unit is used to cyclically adjust the scheme according to each candidate exhibit layout plan until a preset stop condition is reached to obtain the target exhibit layout plan with the optimal exhibit layout effect.

[0173] A method for constructing a digital twin model in a complex scenario. Correspondingly, the present invention also provides a specific embodiment of a device for constructing a digital twin model in a complex scenario.

[0174] Figure 6 Fig. shows the hardware structure schematic diagram of the device for constructing a digital twin model in a complex scenario provided by the embodiment of the present invention.

[0175] The device for constructing a digital twin model in a complex scenario may include a processor 601 and a memory 602 storing computer program instructions.

[0176] Specifically, the above-mentioned processor 601 may include a central processing unit, or a specific integrated circuit, or may be configured as one or more integrated circuits for implementing the embodiments of the present invention.

[0177] The memory 602 may include a mass storage for data or instructions. By way of example and not limitation, the memory 602 may include a hard disk drive, a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus drive, or a combination of two or more of these. Where appropriate, the memory 602 includes removable or non-removable (or fixed) media. Where appropriate, the memory 602 may be internal or external to the digital twin model construction device. In a particular embodiment, the memory 602 is a non-volatile solid-state memory.

[0178] The memory 602 may include a read-only memory, a random access memory, a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory 602 includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present invention.

[0179] The processor 601 reads and executes the computer program instructions stored in the memory 602 to implement the digital twin model construction method in any of the complex scenarios in the above embodiments.

[0180] In one example, the digital twin model construction device in a complex scenario may further include a communication interface 603 and a bus 610. Among them, as Figure 6 shown, the processor 601, the memory 602, and the communication interface 603 are connected through the bus 610 and complete communication with each other.

[0181] The communication interface 603 is mainly used to implement communication between each module, device, unit, and / or device in the embodiments of the present invention.

[0182] The bus 610 includes hardware, software, or both, and couples the components of the case processing device to each other. By way of example and not limitation, the bus may include an accelerated graphics port or other graphics bus, an enhanced industry standard architecture bus, a front-side bus, a hypertransport interconnect, an industry standard architecture bus, an infinite bandwidth interconnect, a low pin count bus, a memory bus, a microchannel architecture bus, a peripheral component interconnect bus, a serial advanced technology attachment bus, a video electronics standards association local bus, or other suitable buses, or a combination of two or more of these. Where appropriate, the bus 610 may include one or more buses. Although the embodiments of the present invention describe and illustrate specific buses, the present invention contemplates any suitable bus or interconnect.

[0183] It should be clear that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present invention.

[0184] It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above steps, that is, the steps can be executed in the order mentioned in the embodiments, or different from the order in the embodiments, or several steps can be executed simultaneously.

[0185] As described above, the above is only the specific implementation manner of the present invention. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules, and units described above can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here. It should be understood that the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope disclosed by the present invention, and these modifications or substitutions should all be covered within the protection scope of the present invention.

Claims

1. A method for constructing a digital twin model in a complex scenario, characterized in that: The method comprises: Acquire layout evaluation parameters corresponding to the target exhibition hall, wherein the layout evaluation parameters include multiple historical exhibit layout schemes and user browsing information under the historical exhibit layout schemes, wherein the user browsing information includes user browsing booths, user entering booth time, and user leaving booth time; Based on the layout evaluation parameters, constructing a layout evaluation function of the target exhibition hall, wherein the layout evaluation function is used to evaluate the exhibit layout effects of various exhibit layout schemes; According to the layout evaluation function, determining the target exhibit layout scheme with the best exhibit layout effect, including: randomly generating multiple initial exhibit layout schemes; determining the fitness corresponding to each of the initial exhibit layout schemes according to the layout evaluation function; screening each of the initial exhibit layout schemes based on the fitness corresponding to each of the initial exhibit layout schemes to obtain the top N candidate exhibit layout schemes with the highest fitness, where N is a positive integer; according to each of the candidate exhibit layout schemes, cyclically adjusting the scheme until a preset stop condition is reached to obtain the target exhibit layout scheme with the best exhibit layout effect; The construction of the layout evaluation function of the target exhibition hall based on the layout evaluation parameters includes: determining the attention of each booth in the target exhibition hall according to the user browsing information under each of the historical exhibit layout schemes; generating a booth change sequence of the target exhibit using each of the historical exhibit layout schemes, wherein the target exhibit is any one of the exhibits in the target exhibition hall, and the booth change sequence is used to characterize the historical booth corresponding to the target exhibit under each of the historical exhibit layout schemes; determining the number of second browsing users corresponding to the target exhibit at each of the historical booths and the target browsing time of each second browsing user according to the booth change sequence and the user browsing information under each of the historical exhibit layout schemes; determining the first priority of the target exhibit according to the number of booths in the booth change sequence, the attention of each historical booth in the booth change sequence, the number of second browsing users and the target browsing time; and determining the first priority of the target exhibit based on the booth change sequence of the target exhibit. According to the position change sequence, the second priority of the target historical exhibit under each of the historical booths corresponding to the target exhibit is obtained, and the target historical exhibit is an exhibit located at the previous historical booth of the target exhibit; according to the first priority of the target exhibit and the second priorities corresponding to the target exhibit, the third priority of the target exhibit is determined; the current booth corresponding to the target exhibit under the current exhibit layout scheme is obtained; the browsing users in the target exhibition hall are tracked to obtain the current number of viewers of the current booth; according to the user browsing information of the target exhibit under each of the historical exhibit layout schemes, the current number of viewers is screened to obtain the number of non-first-time viewers; according to the non-first-time viewers, the current number of viewers and the third priority of the target exhibit, the optimality of the target exhibit is determined; based on the attention of each of the booths in the target exhibition hall and the optimality of each of the exhibits, a layout evaluation function of the target exhibition hall is constructed; Based on the target exhibit layout plan, a digital twin model is constructed.

2. The method for constructing a digital twin model in a complex scenario according to claim 1, characterized in that: The step of obtaining the layout evaluation parameters corresponding to the target exhibition hall includes: Dividing the target exhibition hall according to the booth distribution information to obtain a plurality of exhibition hall areas, each of the exhibition hall areas corresponding to a booth; Acquire a plurality of historical exhibit layout plans, each of the historical exhibit layout plans corresponds to a historical time period, and the duration of each historical time period matches a preset interval duration; The browsing users in the target exhibition hall are tracked to obtain the user browsing booths corresponding to the browsing users under each of the historical exhibit layout schemes, the time when the users enter the booths, and the time when the users leave the booths.

3. The method for constructing a digital twin model in a complex scenario according to claim 2, characterized in that: Determining the attention level of each booth in the target exhibition hall according to the user browsing information under each of the historical exhibit layout plans includes: Based on the user browsing information under each of the historical exhibit layout schemes, determining the number of first browsing users of a target booth and the target browsing time of each first browsing user, the target booth being any one of the booths in the target exhibition hall; The attention degree of the target booth is determined according to the number of the first browsing users and the target browsing time of each of the first browsing users.

4. A digital twin model construction device for complex scenarios, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the method for constructing a digital twin model in a complex scenario as described in any one of claims 1 to 3.

5. A digital twin model construction system for complex scenarios, characterized in that: The system comprises: A parameter acquisition module, used to acquire layout evaluation parameters corresponding to a target exhibition hall, wherein the layout evaluation parameters include a plurality of historical exhibit layout schemes and user browsing information under the historical exhibit layout schemes, wherein the user browsing information includes user browsing booths, user entering booth time, and user leaving booth time; A function construction module, used to construct a layout evaluation function of the target exhibition hall based on the layout evaluation parameters, wherein the layout evaluation function is used to evaluate the exhibit layout effects of various exhibit layout schemes; A scheme determination module is used to determine the target exhibit layout scheme with the best exhibit layout effect according to the layout evaluation function, including: randomly generating multiple initial exhibit layout schemes; determining the fitness corresponding to each of the initial exhibit layout schemes according to the layout evaluation function; screening each of the initial exhibit layout schemes based on the fitness corresponding to each of the initial exhibit layout schemes to obtain the top N candidate exhibit layout schemes with the highest fitness, where N is a positive integer; and cyclically adjusting the scheme according to each of the candidate exhibit layout schemes until a preset stop condition is reached to obtain the target exhibit layout scheme with the best exhibit layout effect; The construction of the layout evaluation function of the target exhibition hall based on the layout evaluation parameters includes: determining the attention of each booth in the target exhibition hall according to the user browsing information under each of the historical exhibit layout schemes; generating a booth change sequence of the target exhibit using each of the historical exhibit layout schemes, wherein the target exhibit is any one of the exhibits in the target exhibition hall, and the booth change sequence is used to characterize the historical booth corresponding to the target exhibit under each of the historical exhibit layout schemes; determining the number of second browsing users corresponding to the target exhibit at each of the historical booths and the target browsing time of each second browsing user according to the booth change sequence and the user browsing information under each of the historical exhibit layout schemes; determining the first priority of the target exhibit according to the number of booths in the booth change sequence, the attention of each historical booth in the booth change sequence, the number of second browsing users and the target browsing time; and determining the first priority of the target exhibit based on the booth change sequence of the target exhibit. According to the position change sequence, the second priority of the target historical exhibit under each of the historical booths corresponding to the target exhibit is obtained, and the target historical exhibit is an exhibit located at the previous historical booth of the target exhibit; according to the first priority of the target exhibit and the second priorities corresponding to the target exhibit, the third priority of the target exhibit is determined; the current booth corresponding to the target exhibit under the current exhibit layout scheme is obtained; the browsing users in the target exhibition hall are tracked to obtain the current number of viewers of the current booth; according to the user browsing information of the target exhibit under each of the historical exhibit layout schemes, the current number of viewers is screened to obtain the number of non-first-time viewers; according to the non-first-time viewers, the current number of viewers and the third priority of the target exhibit, the optimality of the target exhibit is determined; based on the attention of each of the booths in the target exhibition hall and the optimality of each of the exhibits, a layout evaluation function of the target exhibition hall is constructed; The model building module is used to build a digital twin model based on the target exhibit layout plan.

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