Training base construction analysis system and method based on game theory

Abstract

The present disclosure relates to a training base construction analysis system and method based on game theory, and relates to the field of computer technology; based on resource information in the training base construction information, first determine from multiple resources the resources that are of the same resource type and different resource types, that is, the first resource and the second resource, and based on the resource quantity of the first resource and the resource quantity of the second resource, use a preset game theory model to analyze and obtain the resource utilization rate, and then, use the resource utilization rate to optimize the training base construction information. Therefore, the technical solution effectively analyzes the training base construction information based on game theory, and based on the analysis results, effectively optimizes the training base construction information, thereby improving the effect of the training base construction.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular, to a system and method for analyzing the construction of a training base based on game theory. Background Art

[0002] As the demand for practical training grows, more and more regions will build practical training bases to meet the needs of practical training, such as experimental training bases, mechanical equipment training bases, etc. Before establishing a practical training base, it is necessary to conduct a corresponding analysis of the construction needs of the practical training base to determine a more reasonable practical training base construction plan, and then build the practical training base according to the practical training base construction plan.

[0003] At present, after the training base construction plan is determined, there is a lack of an effective analysis method to evaluate whether the training base construction plan is reasonable, which makes the effect of the constructed training base poor in some cases. Summary of the invention

[0004] The purpose of the present invention is to provide a training base construction analysis system and method based on game theory. The training base construction analysis system and method based on game theory can achieve effective optimization of training base construction analysis information based on game theory, thereby improving the effect of training base construction.

[0005] In order to achieve the above-mentioned purpose, in a first aspect, the present disclosure provides a training base construction analysis method based on game theory, including: obtaining training base construction information, the training base construction information including resource information corresponding to multiple resources, each of the resource information including: resource type and resource quantity; according to the resource types corresponding to the multiple resources, determining multiple first resources and multiple second resources from the multiple resources, the multiple first resources are resources belonging to the same resource type, and the multiple second resources are resources belonging to different resource types; determining resource utilization according to the resource quantities corresponding to the multiple first resources, the resource quantities corresponding to the multiple second resources and a preset game theory model; optimizing the training base construction information according to the resource utilization to obtain optimized training base construction information.

[0006] Optionally, determining multiple first resources and multiple second resources from the multiple resources according to the resource types respectively corresponding to the multiple resources includes: generating resource distribution sequences corresponding to multiple resource types respectively according to the resource types respectively corresponding to the multiple resources, different sequence elements in each of the resource distribution sequences are used to characterize resource quantities of different resources; determining a first resource distribution sequence and multiple second resource distribution sequences from the resource distribution sequences respectively corresponding to the multiple resource types; determining the first resource according to the sequence elements in the first resource distribution sequence; and determining the second resource according to the sequence elements in the multiple second resource distribution sequences.

[0007] Optionally, determining a first resource distribution sequence and multiple second resource distribution sequences from the resource distribution sequences respectively corresponding to the multiple resource types includes: for each of the multiple resource distribution sequences, determining a sequence element repetition degree corresponding to the resource distribution sequence according to each sequence element in the resource distribution sequence, the sequence element repetition degree being used to characterize the frequency of occurrence of the same sequence element; determining the first resource distribution sequence from the multiple resource distribution sequences according to the sequence element repetition degrees respectively corresponding to the multiple resource distribution sequences; randomly sampling the multiple resource distribution sequences to obtain randomly sampled resource distribution sequences; and determining multiple second resource distribution sequences from the randomly sampled resource distribution sequences according to the sequence element repetition degrees respectively corresponding to the randomly sampled resource distribution sequences.

[0008] Optionally, the method according to the number of resources corresponding to the multiple first resources, the number of resources corresponding to the multiple second resources and a preset game theory model includes: generating a first game sequence according to the number of resources corresponding to the multiple first resources, the total number of sequence elements of the first game sequence being equal to the sum of the number of resources corresponding to the multiple first resources; generating a second game sequence according to the number of resources corresponding to the multiple second resources and the first game sequence, the total number of sequence elements of the second game sequence being determined according to the total number of sequence elements of the first game sequence and the sum of the number of resources corresponding to the multiple second resources; inputting the first game sequence and the second game sequence into the preset game theory model to obtain a resource interaction rate output by the preset game theory model; and determining the resource utilization rate according to the resource interaction rate.

[0009] Optionally, determining the resource utilization rate based on the resource interaction rate includes: multiplying the resource interaction rate by the sum of the number of resources corresponding to the multiple resources, to determine the number of resources involved in resource interaction; determining the number of resources not involved in resource interaction based on the number of resources involved in resource interaction and the sum of the number of resources corresponding to the multiple resources; determining the resource utilization rate based on the number of resources involved in resource interaction and the number of resources not involved in resource interaction.

[0010] Optionally, the preset game theory model includes: a game theory algorithm module and an interaction rate calculation module, and the inputting the first game sequence and the second game sequence into the preset game theory model to obtain the resource interaction rate output by the preset game theory model includes: inputting the first game sequence and the second game sequence into the game theory algorithm module to obtain multiple selection sequences output by the game theory algorithm module, and the multiple selection sequences correspond to different sequence elements selected from the first game sequence and the second game sequence based on the game theory algorithm; inputting the multiple selection sequences and the first game sequence into the interaction rate calculation module to obtain a first interaction rate; inputting the multiple selection sequences and the second game sequence into the interaction rate calculation module to obtain a second interaction rate; and outputting the resource interaction rate according to the first interaction rate and the second interaction rate through the interaction rate calculation module.

[0011] Optionally, the training base construction information also includes: resource distribution information, the resource distribution information is used to characterize the resource quantities and resource types respectively distributed in multiple resource deployment locations, and the optimization of the training base construction information according to the resource utilization rate to obtain optimized training base construction information includes: determining the resource distribution density according to the resource distribution information; optimizing multiple resource types and / or multiple resource quantities according to the resource utilization rate and the resource distribution density to obtain optimized training base construction information; or, optimizing multiple resource types, multiple resource quantities and at least one of the resource distribution information according to the resource utilization rate to obtain optimized training base construction information.

[0012] Optionally, according to the resource utilization rate and the resource distribution density, multiple resource types and / or multiple resource quantities are optimized to obtain optimized training base construction information, including: if the resource utilization rate is greater than or equal to the preset resource utilization rate, and the resource distribution density is less than or equal to the preset density, adding resources belonging to the new resource type or increasing the number of resources of the first preset resource type; if the resource utilization rate is less than the preset resource utilization rate, and / or the resource distribution density is greater than the preset density, deleting resources belonging to the second preset resource type or reducing the number of resources belonging to the third preset resource type; wherein the first preset resource type, the second preset resource type and the third preset resource type are different.

[0013] Optionally, the training base construction analysis method also includes: obtaining user demand information corresponding to the training base construction information, the user demand information including: demand cost and demand benefit; determining a first cost based on the training base construction information, and determining a first benefit based on the resource utilization rate; determining a second cost and a second benefit based on the optimized training base construction information; determining a cost optimization rate based on the first cost, the second cost and the demand cost; determining a benefit optimization rate based on the first benefit, the second benefit and the demand benefit; generating feedback information based on the cost optimization rate, the benefit optimization rate and the optimized training base construction information, and feeding the feedback information back to the corresponding user end.

[0014] In a second aspect, an embodiment of the present disclosure provides a training base construction analysis system based on game theory, comprising: a client and a server connected to the client in communication; wherein the client is used to receive training base construction information input by a user, and send the training base construction information to the server; the server is used to feedback optimized training base construction information to the client through the training base construction analysis method based on game theory described in the first aspect.

[0015] Through the above technical solution, based on the resource information in the training base construction information, firstly, from multiple resources, resources with randomness belonging to the same resource type and different resource types, that is, the first resource and the second resource, are determined, based on the resource quantity of the first resource and the resource quantity of the second resource, using the preset game theory model, the resource utilization rate is analyzed, and then, the training base construction information is optimized using the resource utilization rate. Therefore, the technical solution effectively analyzes the training base construction information based on game theory, and effectively optimizes the training base construction information based on the analysis results, thereby improving the effect of the training base construction.

[0016] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0018] Figure 1 It is a structural block diagram of a training base construction analysis system based on game theory according to an exemplary embodiment.

[0019] Figure 2 The present invention is an interactive flow chart of a practical training base construction analysis system based on game theory according to an exemplary embodiment.

[0020] Figure 3 It is a flow chart of a method for analyzing the construction of a training base based on game theory according to an exemplary embodiment.

[0021] Figure 4 It is a structural diagram of a game theory model according to an exemplary embodiment.

[0022] Figure 5 It is a block diagram of a training base construction analysis device based on game theory according to an exemplary embodiment.

[0023] Figure 6 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0024] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0025] As the demand for practical training grows, more and more regions will build practical training bases to meet the needs of practical training, such as experimental training bases, mechanical equipment training bases, etc. Before establishing a practical training base, it is necessary to conduct a corresponding analysis of the construction needs of the practical training base to determine a more reasonable practical training base construction plan, and then build the practical training base according to the practical training base construction plan.

[0026] Analysis of training base construction, for example: Environmental construction: The training base should have a virtual simulation training teaching venue that is connected to the actual job operation scenario and equipped with necessary facilities and equipment. This includes the planning of the training site, the selection and configuration of equipment, and the construction of the management platform to ensure the efficiency of resource sharing and teaching management. Resource development: Develop virtual simulation training resources that are connected to actual job skills and standard operation processes. These resources should cover the key skill points in the professional core course training teaching and keep them updated regularly.

[0027] At present, after the training base construction plan is determined, there is a lack of an effective analysis method to evaluate whether the training base construction plan is reasonable, which makes the effect of the constructed training base poor in some cases.

[0028] It is understandable that the construction of a training base may involve multiple dimensions. Regarding the resource dimension, it involves the resource allocation of the training base. If the resource allocation is unreasonable, it may lead to poor construction effects of the training base, for example: low resource utilization and waste of resources.

[0029] Based on this, the embodiment of the present disclosure provides a technical solution, which implements the construction analysis of the training base based on game theory. In addition, the construction of the training base is analyzed from the perspective of resource allocation to maximize the construction effect of the training base.

[0030] Figure 1 is a structural block diagram of a training base construction analysis system based on game theory according to an exemplary embodiment. Figure 1 As shown, the system includes: a client and a server. The client and the server can be connected through a network. The number of clients can be one or more, and the number of servers can also be one or more, and is not limited to Figure 1 shown.

[0031] In some embodiments, the application form of the analysis system can be a training base construction service system, which can be in the form of a website, application program, and mini-program for use by users with needs.

[0032] Figure 2 is an interactive flow chart of a training base construction analysis system based on game theory according to an exemplary embodiment. Figure 2 As shown, the client and the server can realize the analysis of training base construction through interaction.

[0033] Regarding the client, it can be used to implement the human-computer interaction function. For example, a user can register an account through the client and log in through the registered account. After logging in, the system's training base construction analysis function can be used. Therefore, the client can be used to receive the training base construction information input by the user, and send the training base construction information to the server, so that the server analyzes the training base construction information and feeds back the analysis results to the client.

[0034] Therefore, the server can analyze the training base construction information through the technical solution provided by the embodiment of the present disclosure, obtain the analysis result, and feedback the analysis result to the client. The analysis result can be the optimized training base construction information, that is, in the embodiment of the present disclosure, the optimization of the training base construction information can be achieved based on the analysis.

[0035] Furthermore, after receiving the feedback of the optimized training base construction information, the client will display it to the user, and the user can build the training base according to the optimized training base construction information; or, according to the optimized training base construction information, formulate more reasonable training base construction information. That is, the optimized training base construction information can be applied in many ways, which are not limited here.

[0036] The technical solution provided by the embodiment of the present disclosure can be used as a general technical solution, that is, it is applicable to the construction of various types of training bases. Accordingly, the system may need to configure different processing parameters for different types of training bases. It can also be used as a specific technical solution, that is, it is applicable to the construction of a specific type of training base. Accordingly, the system only needs to configure processing parameters for the specific type of training base.

[0037] As an example, this technical solution can be used for the construction analysis of experimental training bases, such as campus experimental training bases, research institute experimental training bases, etc.

[0038] Figure 3 is a flowchart of a method for analyzing the construction of a training base based on game theory according to an exemplary embodiment. Figure 3 As shown, the method comprises the following steps:

[0039] Step 301, obtaining training base construction information. The training base construction information includes resource information corresponding to a plurality of resources, each of which includes: resource type and resource quantity.

[0040] Step 302: Determine a plurality of first resources and a plurality of second resources from the plurality of resources according to the resource types corresponding to the plurality of resources. The plurality of first resources are resources belonging to the same resource type, and the plurality of second resources are resources belonging to different resource types.

[0041] Step 303: Determine resource utilization according to the resource quantities corresponding to the plurality of first resources, the resource quantities corresponding to the plurality of second resources, and a preset game theory model.

[0042] Step 304, optimizing the practical training base construction information according to the resource utilization rate to obtain optimized practical training base construction information.

[0043] In step 301, the training base construction information may be information uploaded by the client, and the information may be uploaded in the form of reports, charts, etc., which are not limited here.

[0044] The training base construction information includes resource information corresponding to a plurality of resources, and the resource information of each resource includes resource type and resource quantity.

[0045] Regarding multiple resources, they can include: real resources and virtual resources. Real resources can be understood as real items, such as experimental items. Virtual resources can be some online resources, such as simulation systems.

[0046] Regarding resource types, they can be resource types defined in the construction of the training base. For example, for an experimental training base, the resource types can be: chemical experimental resources, physical experimental resources, and biological experimental resources. Regarding the number of resources, it can be understood as the number of resources to be configured in the training base. For different types of resources, the quantity may vary greatly. For example, for large equipment, the quantity may be small, while for some basic experimental equipment, the quantity needs to be large.

[0047] In step 302, a plurality of first resources and a plurality of second resources are first determined from the plurality of resources according to the resource types respectively corresponding to the plurality of resources.

[0048] The multiple first resources belong to the same resource type. The multiple second resources belong to different resource types. Therefore, the first resource can be understood as a specific resource under a specific resource type, and the second resource can be understood as a resource under a different resource type.

[0049] In the disclosed embodiments, the analysis of construction information is realized by using a game theory algorithm. The game theory algorithm is a computational method applied in game theory, which is a theory that studies the strategic interaction between decision makers with conflict and cooperation characteristics. In game theory, algorithms are used to analyze and predict the strategies that participants may adopt in different situations, and how these strategies lead to a certain equilibrium state.

[0050] In the disclosed embodiment, the game theory algorithm is used to analyze and predict the resource interaction (selection) strategies that the users of the training base may adopt in different situations.

[0051] Therefore, in order to analyze and predict the resource interaction strategies that participants may adopt in different situations, it is necessary to screen out the first resources and second resources with differences and randomness, use the first resources and the second resources to analyze the resource interaction situation, and then determine the resource utilization rate based on the resource interaction situation.

[0052] It can be understood that the more resource interactions there are, the higher the resource utilization rate is; the less resource interactions there are, the lower the resource utilization rate is. For example, when there are few resource interactions, a single resource can also meet the needs of users, and the existence of most resources is wasted, resulting in low resource utilization rate.

[0053] Therefore, as an optional implementation, step 302 includes: generating resource distribution sequences corresponding to multiple resource types respectively according to the resource types respectively corresponding to the multiple resources, and different sequence elements in each resource distribution sequence are used to characterize the resource quantities of different resources; determining a first resource distribution sequence and multiple second resource distribution sequences from the resource distribution sequences respectively corresponding to the multiple resource types; determining the first resource according to the sequence elements in the first resource distribution sequence; and determining the second resource according to the sequence elements in the multiple second resource distribution sequences.

[0054] In this embodiment, the resource type is quantified into a resource distribution sequence, so as to determine the first resource and the second resource having difference and randomness based on the resource distribution sequence.

[0055] In some embodiments, multiple resources under each resource type are first determined, and then the quantities of the multiple resources are used as sequence elements. For example, if the resource distribution sequence is: [100, 50, 20, 20, 40], it means that the resource type includes 5 resources, and the quantities of the 5 resources are: 100, 50, 20, 20 and 40 respectively. Through the resource distribution sequence, the distribution of each resource type can be seen.

[0056] In some embodiments, the above-mentioned resource quantities may correspond to resource identification codes, which are used to characterize resources. In this way, a resource distribution sequence such as [100-001, 50-002, 20-003, 20-004, 40-005] may be established, in which 001 to 005 may be understood as resource identification codes.

[0057] Furthermore, determining a first resource distribution sequence and multiple second resource distribution sequences from resource distribution sequences corresponding to multiple resource types respectively may include: for each resource distribution sequence in the multiple resource distribution sequences, determining a sequence element repetition degree corresponding to the resource distribution sequence according to each sequence element in the resource distribution sequence, the sequence element repetition degree being used to characterize the frequency of occurrence of the same sequence element; determining a first resource distribution sequence from the multiple resource distribution sequences according to the sequence element repetition degrees corresponding to the multiple resource distribution sequences respectively; performing random sampling on the multiple resource distribution sequences to obtain randomly sampled resource distribution sequences; and determining multiple second resource distribution sequences from the randomly sampled resource distribution sequences according to the sequence element repetition degrees corresponding to the randomly sampled resource distribution sequences respectively.

[0058] In some embodiments, the sequence element repetition degree is the repetition degree of the sequence element representing the number of resources, that is, when calculating the repetition degree, the resource identification code is not considered.

[0059] In some embodiments, statistics are collected on repeated sequence elements in the resource distribution sequence to determine the number of repeated sequence elements, and the ratio of the number of repeated sequence elements to the total number of sequence elements is determined as the repetition degree.

[0060] Furthermore, the resource distribution sequence with the lowest degree of repetition may be determined as the first resource distribution sequence. If there are multiple resource distribution sequences with the lowest degree of repetition, a resource distribution sequence with a larger number of sequence elements is selected as the first resource distribution sequence.

[0061] In some embodiments, a plurality of resource distribution sequences are randomly sampled to obtain a randomly sampled resource distribution sequence, and the random sampling method may adopt mature technology in the art.

[0062] In some embodiments, the randomly sampled resource distribution sequences are sorted from low to high according to the repetition of sequence elements, and the resource distribution sequences ranked in the top 10% (or other values, according to the application scenario configuration) are selected; and the sequence elements are sorted from high to low according to the number of sequence elements, and the resource distribution sequences ranked in the top 10% (or other values, according to the application scenario configuration) are selected. The resource distribution sequences obtained by the two selection methods are deduplicated to obtain a second resource distribution sequence.

[0063] Furthermore, resources corresponding to some or all sequence elements in the first resource sequence may be determined as first resources. Also, a plurality of second resource distribution sequences are randomly sampled (it is necessary to ensure that each resource distribution sequence is sampled) to obtain randomly sampled sequence elements, and second resources are determined based on the resources corresponding to the randomly sampled sequence elements.

[0064] Through the above implementation, the difference and randomness of the first resource and the second resource can be fully guaranteed.

[0065] In step 303, the resource utilization rate is determined according to the resource quantities corresponding to the plurality of first resources, the resource quantities corresponding to the plurality of second resources, and a preset game theory model.

[0066] As an optional implementation, step 303 includes: generating a first game sequence according to the number of resources corresponding to multiple first resources, the total number of sequence elements of the first game sequence being equal to the sum of the number of resources corresponding to the multiple first resources; generating a second game sequence according to the number of resources corresponding to multiple second resources and the first game sequence, the total number of sequence elements of the second game sequence being determined according to the total number of sequence elements of the first game sequence and the sum of the number of resources corresponding to the multiple second resources; inputting the first game sequence and the second game sequence into a preset game theory model to obtain a resource interaction rate output by the preset game theory model; and determining the resource utilization rate according to the resource interaction rate.

[0067] In this implementation, the sequence elements of the first game sequence may be resource identification codes of the respective first resources. For example, assuming that there are three first resources, and the numbers are 2, 3, and 4 respectively, the generated first game sequence may be: [001, 001, 002, 002, 002, 003, 003, 003, 003, 003], where 001 to 003 are the resource identification codes of the three resources respectively. Therefore, the total number of sequence elements of the first game sequence is equal to the sum of the number of resources corresponding to the multiple first resources respectively.

[0068] In some embodiments, if the total number of sequence elements of the first game sequence is less than or equal to the sum of the number of resources corresponding to the multiple second resources, the total number of sequence elements of the second game sequence is equal to the sum of the number of resources corresponding to the multiple second resources, and the second game sequence is generated in the same manner as the first game sequence. If the total number of sequence elements of the first game sequence is greater than or equal to the sum of the number of resources corresponding to the multiple second resources, the total number of sequence elements of the second game sequence is greater than the sum of the number of resources corresponding to the multiple second resources. Therefore, the initial game sequence can be generated in the same manner as the first game sequence, and then the game sequence can be expanded to increase the number of sequence elements to generate the final second game sequence.

[0069] The expansion method includes, for example, randomly adding sequence elements, where the added sequence elements are equal to the existing sequence elements.

[0070] Through this implementation, the number of sequence elements in the first game sequence and the second game sequence can be different, thereby increasing the diversity of the game algorithm.

[0071] Furthermore, the first game sequence and the second game sequence are input into a preset game theory model, so that the game theory model can output a resource interaction rate.

[0072] Figure 4is a schematic diagram of a game theory model according to an exemplary embodiment. Figure 4 As shown, the preset game theory model includes: a game theory algorithm module and an interaction rate calculation module.

[0073] As an optional implementation, the first game sequence and the second game sequence are input into a preset game theory model to obtain a resource interaction rate output by the preset game theory model, including: inputting the first game sequence and the second game sequence into a game theory algorithm module to obtain multiple selection sequences output by the game theory algorithm module, the multiple selection sequences corresponding to different sequence elements selected from the first game sequence and the second game sequence based on the game theory algorithm; inputting the multiple selection sequences and the first game sequence into an interaction rate calculation module to obtain a first interaction rate; inputting the multiple selection sequences and the second game sequence into the interaction rate calculation module to obtain a second interaction rate; and outputting the resource interaction rate according to the first interaction rate and the second interaction rate through the interaction rate calculation module.

[0074] In some embodiments, the game theory algorithm module is a module based on the game theory algorithm, which can implement the corresponding game theory algorithm. For example, the game theory algorithm performs multiple selections based on the first game sequence and the second game sequence to obtain multiple selection combinations, and each selection combination corresponds to a selection sequence. That is, the multiple selection sequences correspond to different sequence elements obtained by selecting from the first game sequence and the second game sequence based on the game theory algorithm.

[0075] In some embodiments, the game theory algorithm may be: Bash game algorithm, Wizov game algorithm, Nim game algorithm, etc. Different game theory algorithms have different game principles, and correspondingly, the obtained selection sequences are also different. In the embodiments of the present disclosure, a suitable game theory algorithm can be configured according to the requirements, and the game principles of the game theory algorithm can refer to the mature technology in the field.

[0076] Thus, the game theory algorithm module can output multiple selection sequences, and it can be understood that each selection sequence can represent resources with interactive relationships.

[0077] Thus, multiple selection sequences and the first game sequence are input into the interaction rate calculation module to obtain a first interaction rate, and multiple selection sequences and the second game sequence are input into the interaction rate calculation module to obtain a second interaction rate.

[0078] In some embodiments, the interaction rate calculation module is used to calculate the interaction rate according to a preset calculation principle.

[0079] In some embodiments, the first interaction rate may be a repetition rate of sequence elements between the plurality of selection sequences and the first game sequence, and the second interaction rate may be a repetition rate of sequence elements between the plurality of selection sequences and the second game sequence.

[0080] Further, the interaction rate calculation module determines the resource interaction rate according to the first interaction rate and the second interaction rate. In some embodiments, the average value of the first interaction rate and the second interaction rate can be determined as the resource interaction rate. Alternatively, the weighted value of the first interaction rate and the second interaction rate can be determined as the resource interaction rate, which is not limited here.

[0081] After determining the resource interaction rate, further determining the resource utilization rate. In some embodiments, determining the resource utilization rate includes: multiplying the resource interaction rate by the sum of the number of resources corresponding to the multiple resources to determine the number of resources involved in resource interaction; determining the number of resources not involved in resource interaction based on the number of resources involved in resource interaction and the sum of the number of resources corresponding to the multiple resources; determining the resource utilization rate based on the number of resources involved in resource interaction and the number of resources not involved in resource interaction.

[0082] In some embodiments, the number of resources not involving resource interaction is obtained by subtracting the number of resources involving resource interaction from the sum of the number of resources corresponding to the plurality of resources.

[0083] In some embodiments, the ratio of the number of resources not involving resource interaction to the number of resources involving resource interaction is determined as the resource utilization rate.

[0084] In other embodiments, the resource interaction rate may be directly determined as the resource utilization rate.

[0085] Furthermore, in step 304, the training base construction information is optimized according to the resource utilization rate to obtain optimized training base construction information.

[0086] As an optional implementation, the training base construction information further includes: resource distribution information, where the resource distribution information is used to characterize the quantity and type of resources respectively distributed in a plurality of resource deployment locations.

[0087] Resource distribution information may be represented by a resource distribution map. For example, a plurality of resource deployment positions are set on the resource distribution map, and each resource deployment position is marked with resource quantity and resource type information.

[0088] The resource deployment location can be a deployment location based on the three-dimensional model of the training base. It is understandable that before the construction of the training base, a three-dimensional model can be established first, so resource information can be marked based on the three-dimensional model. It is understandable that the number of resources marked here is the total number of deployed resources, and does not involve the number of specific resources.

[0089] Correspondingly, step 304 may include: determining the resource distribution density based on the resource distribution information; optimizing multiple resource types and / or multiple resource quantities based on the resource utilization rate and the resource distribution density to obtain optimized training base construction information; or, optimizing at least one of the multiple resource types, multiple resource quantities and resource distribution information based on the resource utilization rate to obtain optimized training base construction information.

[0090] In this implementation, the resource distribution density may be determined first according to the resource distribution information, so as to optimize multiple resource types and / or multiple resource quantities in combination with the resource utilization rate and the resource distribution density. Alternatively, at least one of the multiple resource types, multiple resource quantities and resource distribution information may be optimized directly according to the resource utilization rate.

[0091] In some embodiments, determining the resource distribution density includes: calculating the similarity of resource distribution conditions of adjacent resource deployment locations, and converting the similarity into resource distribution density. For example, the higher the similarity, the higher the resource distribution density.

[0092] Among them, the distance between adjacent resource deployment locations is less than the preset distance. For example, if the area of ​​the training base is 2,500 square meters, the preset distance may be 2 meters. The preset distance may be a horizontal distance or a vertical distance, for example, different floors of the same building.

[0093] In some embodiments, several adjacent resource deployment locations belonging to different directions or different regions are selected, similarities are calculated respectively, multiple similarities are integrated, a final similarity is determined, and converted into resource distribution density.

[0094] Furthermore, based on resource utilization and resource distribution density, multiple resource types and / or multiple resource quantities are optimized to obtain optimized training base construction information, which may include: if the resource utilization is greater than or equal to the preset resource utilization, and the resource distribution density is less than or equal to the preset density, adding resources belonging to the new resource type or increasing the number of resources of the first preset resource type; if the resource utilization is less than the preset resource utilization, and / or the resource distribution density is greater than the preset density, deleting resources belonging to the second preset resource type or reducing the number of resources belonging to the third preset resource type; wherein the first preset resource type, the second preset resource type and the third preset resource type are different.

[0095] In some embodiments, the preset resource utilization rate can be set according to different application scenarios. For example, the larger the area of ​​the training base, the higher the preset resource utilization rate; the greater the geographical location advantage of the training base, the higher the preset resource utilization rate.

[0096] In some embodiments, the preset density can be set according to different application scenarios. For example, the larger the area of ​​the training base, the lower the preset density; the more complex the terrain of the training base, the higher the preset density.

[0097] In some embodiments, the first preset resource type may be a basic resource type, which is used more frequently. The second preset resource type may be a rare resource type, which is used nearly 0 frequently. The third preset resource type may be a common resource type, which is used neither frequently nor less frequently.

[0098] In some embodiments, the user may pre-define three preset resource types, and when optimization is needed, the corresponding information optimization is directly performed for the defined preset resource types.

[0099] In some embodiments, the occurrence frequencies of various preset resource types in the training base construction information that has been processed in the system can also be counted, and based on these occurrence frequencies, the first preset resource type, the second preset resource type, and the third preset resource type are determined. In addition, the determined first preset resource type, the second preset resource type, and the third preset resource type can be updated as the system data increases.

[0100] In some embodiments, the optimized training base construction information can be directly fed back to the user end (ie, the client) for user reference.

[0101] In some embodiments, more meaningful feedback information may be generated.

[0102] Therefore, the training base construction analysis method may also include: obtaining user demand information corresponding to the training base construction information, the user demand information including: demand cost and demand benefit; determining the first cost according to the training base construction information, and determining the first benefit according to the resource utilization rate; determining the second cost and the second benefit according to the optimized training base construction information; determining the cost optimization rate according to the first cost, the second cost and the demand cost; determining the benefit optimization rate according to the first benefit, the second benefit and the demand benefit; generating feedback information according to the cost optimization rate, the benefit optimization rate and the optimized training base construction information, and feeding the feedback information back to the corresponding user end.

[0103] In some embodiments, user demand information corresponding to the practical training base construction information may be uploaded together with the user uploading the practical training base construction information.

[0104] In some embodiments, the required cost may represent the cost of building a training base that is acceptable to users, and the required benefit may represent the benefit after the construction of the training base that is acceptable to users, which may be monetary benefit or non-monetary benefit.

[0105] In some embodiments, the first cost may be determined based on the training base construction information. Specifically, the construction costs of various resources may be estimated in the system, and the first cost may be determined based on the estimated construction costs and the training base construction information.

[0106] In some embodiments, the revenues corresponding to different resource utilization rates may be preset, and the corresponding revenues may be determined according to the current resource utilization rate, wherein the higher the resource utilization rate, the higher the revenue.

[0107] In some embodiments, the implementation method of determining the second cost based on the optimized training base construction information may be the same as the implementation method of determining the first cost.

[0108] In some embodiments, the second benefit is determined according to the optimized training base construction information and the estimated construction benefits of various resources. That is, the system can also estimate the construction benefits of various resources.

[0109] In some embodiments, cost optimization rate = (first cost / demand cost) / (second cost / demand cost). Revenue optimization rate = (first revenue / demand revenue) / (second revenue / demand revenue).

[0110] Furthermore, the cost optimization rate, the revenue optimization rate and the optimized training base construction information are integrated into feedback information and fed back to the corresponding user end.

[0111] Through this implementation method, users can understand the optimization situation and then make better use of the optimized training base construction information.

[0112] Through the above technical solution, based on the resource information in the training base construction information, firstly, from multiple resources, resources with randomness belonging to the same resource type and different resource types, that is, the first resource and the second resource, are determined, based on the resource quantity of the first resource and the resource quantity of the second resource, using the preset game theory model, the resource utilization rate is analyzed, and then, the training base construction information is optimized using the resource utilization rate. Therefore, the technical solution effectively analyzes the training base construction information based on game theory, and effectively optimizes the training base construction information based on the analysis results, thereby improving the effect of the training base construction.

[0113] Figure 5 The present invention is a block diagram of a training base construction analysis device based on game theory according to an exemplary embodiment, comprising:

[0114] The acquisition module 501 is used to acquire the construction information of the training base, wherein the construction information of the training base includes resource information corresponding to a plurality of resources, each of which includes: resource type and resource quantity.

[0115] The analysis module 502 is used to determine a plurality of first resources and a plurality of second resources from the plurality of resources according to the resource types respectively corresponding to the plurality of resources, the plurality of first resources being resources belonging to the same resource type, and the plurality of second resources being resources belonging to different resource types; determine resource utilization according to the number of resources respectively corresponding to the plurality of first resources, the number of resources respectively corresponding to the plurality of second resources, and a preset game theory model; and optimize the training base construction information according to the resource utilization to obtain optimized training base construction information.

[0116] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0117] Figure 6 6 is a block diagram of an electronic device 600 according to an exemplary embodiment. For example, the electronic device 600 may be provided as a server. Figure 6 The electronic device 600 includes a processor 622, which may be one or more, and a memory 632 for storing a computer program executable by the processor 622. The computer program stored in the memory 632 may include one or more modules, each corresponding to a set of instructions. In addition, the processor 622 may be configured to execute the computer program to perform the above-mentioned game theory-based training base construction analysis method.

[0118] In addition, the electronic device 600 may further include a power supply component 626 and a communication component 650, wherein the power supply component 626 may be configured to perform power management of the electronic device 600, and the communication component 650 may be configured to implement communication of the electronic device 600, for example, wired or wireless communication. In addition, the electronic device 600 may further include an input / output (I / O) interface 658. The electronic device 600 may operate based on an operating system stored in the memory 632, such as Windows ServerTM, Mac OSXTM, UnixTM, LinuxTM, etc.

[0119] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned training base construction analysis method based on game theory are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 632 including program instructions, and the above-mentioned program instructions can be executed by the processor 622 of the electronic device 600 to complete the above-mentioned training base construction analysis method based on game theory.

[0120] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a processor, and when the computer program is executed by the processor, the steps of the above-mentioned game theory-based training base construction analysis method are implemented.

[0121] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0122] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0123] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A method for analyzing the construction of a training base based on game theory. It is characterized in that include: Acquire training base construction information, the training base construction information includes resource information corresponding to a plurality of resources, each of the resource information includes: resource type and resource quantity; Determine a plurality of first resources and a plurality of second resources from the plurality of resources according to resource types respectively corresponding to the plurality of resources, the plurality of first resources being resources belonging to the same resource type, and the plurality of second resources being resources belonging to different resource types; Determine resource utilization according to the resource quantities respectively corresponding to the plurality of first resources, the resource quantities respectively corresponding to the plurality of second resources, and a preset game theory model; Optimizing the training base construction information according to the resource utilization rate to obtain optimized training base construction information; The determining of resource utilization according to the resource quantities respectively corresponding to the plurality of first resources, the resource quantities respectively corresponding to the plurality of second resources and a preset game theory model comprises: Generate a first game sequence according to the resource quantities respectively corresponding to the multiple first resources, wherein the total number of sequence elements of the first game sequence is equal to the sum of the resource quantities respectively corresponding to the multiple first resources; Generate a second game sequence according to the number of resources respectively corresponding to the multiple second resources and the first game sequence, wherein the total number of sequence elements of the second game sequence is determined according to the sum of the total number of sequence elements of the first game sequence and the number of resources respectively corresponding to the multiple second resources; Inputting the first game sequence and the second game sequence into the preset game theory model to obtain a resource interaction rate output by the preset game theory model; Determining the resource utilization rate according to the resource interaction rate; Determining the resource utilization rate according to the resource interaction rate includes: Multiplying the resource interaction rate by the sum of the resource quantities corresponding to the multiple resources respectively, to determine the number of resources involved in resource interaction; Determining the number of resources not involved in resource interaction according to the number of resources involved in resource interaction and the sum of the number of resources respectively corresponding to the multiple resources; Determining the resource utilization rate according to the number of resources involved in resource interaction and the number of resources not involved in resource interaction; The preset game theory model includes: a game theory algorithm module and an interaction rate calculation module, and the first game sequence and the second game sequence are input into the preset game theory model to obtain the resource interaction rate output by the preset game theory model, including: Inputting the first game sequence and the second game sequence into the game theory algorithm module to obtain a plurality of selection sequences output by the game theory algorithm module, wherein the plurality of selection sequences correspond to different sequence elements selected from the first game sequence and the second game sequence based on the game theory algorithm; Inputting the plurality of selection sequences and the first game sequence into the interaction rate calculation module to obtain a first interaction rate; Inputting the plurality of selection sequences and the second game sequence into the interaction rate calculation module to obtain a second interaction rate; The resource interaction rate is outputted by the interaction rate calculation module according to the first interaction rate and the second interaction rate.

2. According to the training base construction analysis method of claim 1, It is characterized in that The determining a plurality of first resources and a plurality of second resources from the plurality of resources according to the resource types respectively corresponding to the plurality of resources comprises: Generate resource distribution sequences corresponding to the resource types respectively according to the resource types respectively corresponding to the multiple resources, wherein different sequence elements in each of the resource distribution sequences are used to represent the resource quantities of different resources; Determining a first resource distribution sequence and a plurality of second resource distribution sequences from the resource distribution sequences respectively corresponding to the plurality of resource types; determining the first resource according to a sequence element in the first resource distribution sequence; The second resource is determined according to sequence elements in the plurality of second resource distribution sequences.

3. According to the training base construction analysis method of claim 2, It is characterized in that The step of determining a first resource distribution sequence and a plurality of second resource distribution sequences from the resource distribution sequences respectively corresponding to the plurality of resource types comprises: For each of the resource distribution sequences in the plurality of resource distribution sequences, determining a sequence element repetition degree corresponding to the resource distribution sequence according to each sequence element in the resource distribution sequence, wherein the sequence element repetition degree is used to characterize the occurrence frequency of the same sequence element; determining the first resource distribution sequence from the multiple resource distribution sequences according to the repetition degrees of sequence elements respectively corresponding to the multiple resource distribution sequences; Randomly sampling the multiple resource distribution sequences to obtain randomly sampled resource distribution sequences; According to the repetition degrees of sequence elements respectively corresponding to the randomly sampled resource distribution sequences, a plurality of the second resource distribution sequences are determined from the randomly sampled resource distribution sequences.

4. The training base construction analysis method according to claim 1, It is characterized in that The training base construction information further includes: resource distribution information, the resource distribution information is used to characterize the resource quantity and resource type respectively distributed in a plurality of resource deployment positions, and the training base construction information is optimized according to the resource utilization rate to obtain the optimized training base construction information, including: Determine resource distribution density according to the resource distribution information; optimize multiple resource types and / or multiple resource quantities according to the resource utilization rate and the resource distribution density to obtain optimized training base construction information; or, According to the resource utilization rate, at least one of the multiple resource types, multiple resource quantities and the resource distribution information is optimized to obtain optimized training base construction information.

5. According to the training base construction analysis method of claim 4, It is characterized in that The optimizing of multiple resource types and / or multiple resource quantities according to the resource utilization rate and the resource distribution density to obtain optimized training base construction information includes: If the resource utilization is greater than or equal to a preset resource utilization, and the resource distribution density is less than or equal to a preset density, adding resources belonging to a new resource type or increasing the number of resources of the first preset resource type; If the resource utilization is less than a preset resource utilization, and / or the resource distribution density is greater than a preset density, deleting resources belonging to the second preset resource type or reducing the number of resources belonging to the third preset resource type; The first preset resource type, the second preset resource type and the third preset resource type are different.

6. The training base construction analysis method according to claim 1, It is characterized in that The training base construction analysis method also includes: Acquire user demand information corresponding to the training base construction information, the user demand information including: demand cost and demand benefit; Determine a first cost according to the training base construction information, and determine a first benefit according to the resource utilization rate; Determining a second cost and a second benefit according to the optimized practical training base construction information; determining a cost optimization rate according to the first cost, the second cost, and the demand cost; determining a revenue optimization rate according to the first revenue, the second revenue, and the required revenue; Feedback information is generated according to the cost optimization rate, the revenue optimization rate and the optimized training base construction information, and the feedback information is fed back to the corresponding user terminal.

7. A training base construction analysis system based on game theory, It is characterized in that include: A client and a server connected to the client for communication; Among them, the client is used to receive the training base construction information input by the user and send the training base construction information to the server; the server is used to feedback the optimized training base construction information to the client through the training base construction analysis method based on game theory described in any one of claims 1-6.

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