Efficiency evaluation analysis method and system for air-ground game

Abstract

The invention discloses an air-ground game-oriented efficiency evaluation analysis method and system, and the method comprises the steps: determining efficiency evaluation elements according to user demands, and obtaining simulation result data; processing the performance evaluation elements to obtain a performance evaluation element weight matrix; and based on an efficiency evaluation model, processing the efficiency evaluation element weight matrix and the simulation result data to obtain an efficiency evaluation result. According to the air-ground game-oriented efficiency evaluation analysis method and system provided by the invention, simulation result data can be flexibly selected according to user requirements, the air-ground game efficiency is evaluated by comprehensively using the efficiency evaluation model and the efficiency evaluation element weight, and the urgent requirements of air-ground game efficiency evaluation in a complex environment are met.

Description

Technical Field

[0001] The present invention relates to the field of modeling and simulation, and in particular to an efficiency evaluation and analysis method and system for air-ground game. Background Art

[0002] With the rapid development of information and networking technology, the composition and use of systems are becoming more and more complex, involving many random and non-random factors in the use of equipment. Especially under complex environmental conditions, system performance evaluation must not only consider the system's own functional performance, internal characteristics, working mechanism and other factors, but also consider the impact of complex environmental elements and the interaction during the game. At present, there is a lack of performance evaluation and analysis methods for specific simulation systems that combine complex environmental factors with application scenarios. Therefore, high requirements are placed on the establishment of a performance indicator system and the selection of performance evaluation methods. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a performance evaluation and analysis method and system for air-ground game, which can flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and performance evaluation factor weights to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0004] In order to solve the above technical problems, the first aspect of the embodiment of the present invention discloses a performance evaluation and analysis method for air-ground game, characterized in that the method includes:

[0005] S1, determine the performance evaluation factors according to user needs and obtain simulation result data;

[0006] S2, processing the performance evaluation factors to obtain a performance evaluation factor weight matrix;

[0007] S3, based on the performance evaluation model, processing the performance evaluation factor weight matrix and the simulation result data to obtain a performance evaluation result.

[0008] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the processing of the performance evaluation elements to obtain a performance evaluation element weight matrix includes:

[0009] S21, analyzing and processing the performance evaluation factors to obtain a set of indicators to be evaluated;

[0010] S22, using the weight determination model to process the parameter set of the indicator to be evaluated to obtain a first weight set;

[0011] S23, processing the set of indicators to be evaluated to obtain a first judgment matrix;

[0012] S24, using the first weight set, processing the first judgment matrix to obtain a second judgment matrix;

[0013] S25, performing characteristic vector calculation processing on the second judgment matrix to obtain a performance evaluation factor weight matrix.

[0014] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the processing of the set of indicators to be evaluated to obtain a first judgment matrix includes:

[0015] S231, performing pairwise comparison and judgment on the set of indicators to be evaluated to obtain a preprocessing judgment result;

[0016] S232: Using a consistency judgment model, perform consistency check processing on the preprocessing judgment result to obtain a first judgment matrix.

[0017] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the consistency judgment model expression is:

[0018] A=(a ij ) n×n a ij >0,a ji =1 / a ij , i, j = 1, 2, ... n;

[0019] a ij =a ik a kj ,i,j,k=1,2,...,n;

[0020]

[0021] Among them, CR represents the consistency ratio; CI represents the consistency index; RI represents the average random consistency index; λ max represents the maximum characteristic root of A; A represents the first judgment matrix; a ij represents the scale of the i-th indicator to be evaluated with respect to the j-th indicator to be evaluated; a ji represents the scale of the jth indicator to be evaluated with respect to the ith indicator to be evaluated; a ik represents the scale of the i-th indicator to be evaluated with respect to the k-th indicator to be evaluated; a kj It represents the scale of the kth indicator to be evaluated with respect to the jth indicator to be evaluated; n represents the number of indicators to be evaluated.

[0022] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the using the first weight set to process the first judgment matrix to obtain a second judgment matrix includes:

[0023] Using a second judgment matrix to obtain a model, the first weight set and the first judgment matrix are processed to obtain a comprehensive judgment matrix;

[0024] The second judgment matrix acquisition model expression is:

[0025]

[0026]

[0027] in, represents the second judgment matrix; represents the kth first judgment matrix; k represents the weight of the kth first judgment matrix, and λ k ≥0, m represents the number of the first judgment matrix.

[0028] As an optional implementation, in the first aspect of the embodiment of the present invention, the performance evaluation factor weight matrix and the simulation result data are processed based on the performance evaluation model to obtain the performance evaluation result, including:

[0029] S31, analyzing and processing the simulation result data to obtain first simulation result data, second simulation result data, third simulation result data, fourth simulation result data, fifth simulation result data, sixth simulation result data and seventh simulation result data;

[0030] S32, processing the performance evaluation factor weight matrix to obtain a first weight value, a second weight value, a third weight value, a fourth weight value, a fifth weight value, a sixth weight value, a seventh weight value and an eighth weight value;

[0031] S33, based on the performance evaluation model, the first simulation result data, the second simulation result data, the third simulation result data, the fourth simulation result data, the fifth simulation result data, the sixth simulation result data, the seventh simulation result data, the first weight value, the second weight value, the third weight value, the fourth weight value, the fifth weight value, the sixth weight value, the seventh weight value and the eighth weight value are processed to obtain a performance evaluation result.

[0032] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the first simulation result data, the second simulation result data, the third simulation result data, the fourth simulation result data, the fifth simulation result data, the sixth simulation result data, the seventh simulation result data, the first weight value, the second weight value, the third weight value, the fourth weight value, the fifth weight value, the sixth weight value, the seventh weight value and the eighth weight value are processed based on the performance evaluation model to obtain a performance evaluation result, including:

[0033] S331, acquiring first performance evaluation information based on the first simulation result data;

[0034] Based on the second simulation result data, obtaining second performance evaluation information;

[0035] Processing the third simulation result data and the first weight value to obtain third performance evaluation information;

[0036] Processing the fourth simulation result data and the second weight value to obtain fourth performance evaluation information;

[0037] Processing the fifth simulation result data and the third weight value to obtain fifth performance evaluation information;

[0038] Processing the sixth simulation result data and the fourth weight value to obtain sixth performance evaluation information;

[0039] Processing the seventh simulation result data and the fifth weight value to obtain seventh performance evaluation information;

[0040] S332, processing the third performance evaluation information and the fourth performance evaluation information to obtain eighth performance evaluation information;

[0041] Processing the fifth performance evaluation information, the sixth performance evaluation information, and the seventh performance evaluation information to obtain ninth performance evaluation information;

[0042] S333, processing the second performance evaluation information and the sixth weight value to obtain tenth performance evaluation information;

[0043] Processing the third performance evaluation information and the fourth performance evaluation information to obtain eleventh performance evaluation information;

[0044] Processing the fifth performance evaluation information, the sixth performance evaluation information, and the seventh performance evaluation information to obtain twelfth performance evaluation information;

[0045] S334, processing the tenth performance evaluation information, the eleventh performance evaluation information and the twelfth performance evaluation information to obtain comprehensive performance evaluation information;

[0046] S335, multiplying the first performance evaluation information and the comprehensive performance evaluation information to obtain a performance evaluation result.

[0047] A second aspect of an embodiment of the present invention discloses a system for evaluating and analyzing the effectiveness of an air-ground game, wherein the system comprises:

[0048] A data acquisition module, a first processing module and a second processing module;

[0049] The data acquisition module is used to determine the performance evaluation factors according to user needs and obtain simulation result data;

[0050] The first processing module is used to process the performance evaluation elements to obtain a performance evaluation element weight matrix;

[0051] The second processing module is used to process the performance evaluation factor weight matrix and the simulation result data based on the performance evaluation model to obtain a performance evaluation result.

[0052] The third aspect of the present invention discloses a performance evaluation and analysis device for air-ground game, the device comprising:

[0053] A memory storing executable program code;

[0054] a processor coupled to the memory;

[0055] The processor calls the executable program code stored in the memory to execute part or all of the steps in the performance evaluation and analysis method for space-land game disclosed in the first aspect of the embodiment of the present invention.

[0056] The fourth aspect of the present invention discloses a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, and when the computer instructions are called, some or all of the steps in the performance evaluation and analysis method for space-land game disclosed in the first aspect of the embodiment of the present invention are executed.

[0057] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0058] In the embodiment of the present invention, simulation result data can be flexibly selected according to user needs, and the game effectiveness in a complex environment can be evaluated by comprehensively using the performance evaluation model and the performance evaluation factor weights, thereby meeting the urgent needs of air-ground game effectiveness evaluation in a complex environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0060] Figure 1 It is a scene schematic diagram of the performance evaluation and analysis system for air-ground game provided by an embodiment of the present invention;

[0061] Figure 2 It is a flow chart of a method for evaluating and analyzing the effectiveness of an air-ground game disclosed in an embodiment of the present invention;

[0062] Figure 3 It is a structural schematic diagram of a system for evaluating and analyzing the effectiveness of air-ground games disclosed in an embodiment of the present invention;

[0063] Figure 4 It is a structural schematic diagram of another performance evaluation and analysis device for air-ground game disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0066] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0067] In this application, the word "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described in this application as "exemplary" is not necessarily to be construed as being preferred or advantageous over other embodiments. The following description is given to enable any technician in the field to implement and use the present application. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present application can be implemented without using these specific details. In other instances, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present application with unnecessary details. Therefore, the present application is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present application.

[0068] It should be noted that since the method of the embodiment of the present application is executed in a computer device, the processing objects of each computer device exist in the form of data or information. For example, time is actually time information. It can be understood that if size, quantity, position, etc. are mentioned in subsequent embodiments, they are all corresponding data for processing by the computer device. The details will not be repeated here.

[0069] It should be noted that the artificial intelligence related technologies that may be involved in this application are briefly described. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines so that machines have the functions of perception, reasoning and decision-making.

[0070] Artificial intelligence technology is a comprehensive discipline that covers a wide range of fields, including both hardware-level and software-level technologies. The basic technologies of artificial intelligence generally include sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics and other technologies. Artificial intelligence software technology mainly includes computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0071] Computer Vision (CV) is a science that studies how to make machines "see". To put it more specifically, it refers to machine vision such as using cameras and computers to replace human eyes to identify and measure targets, and further processing graphics so that the computer processing becomes an image that is more suitable for human observation or transmission to instruments for detection. As a scientific discipline, computer vision studies related theories and technologies, and attempts to establish an artificial intelligence system that can obtain information from images or multi-dimensional data. Computer vision technology usually includes image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, three-dimensional object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous positioning and map construction, and other technologies, as well as common biometric recognition technologies such as face recognition and fingerprint recognition.

[0072] Unimodal information is data of only one type, such as text, image, audio, video, electromagnetic signal, etc. Multimodal information is data that includes at least two types of unimodal information. Furthermore, multimodal information is suitable for complex tasks that require the integration of multiple information sources, such as sentiment analysis, robot interaction, autonomous driving, etc. By integrating information from multiple modalities, higher performance and accuracy can usually be achieved on the task.

[0073] A large model refers to an artificial neural network model with a very large number of parameters. In the field of artificial intelligence, a large model generally refers to a model with hundreds of millions to trillions of parameters. Models usually need to be trained on large-scale data sets and require a large amount of computing resources to be optimized and adjusted. Large models are often used to solve complex tasks such as natural language processing, computer vision, and speech recognition. Generative AI is an AI that can create new content and ideas, including conversations, stories, images, videos, and music. In an embodiment of the present application, the large model may be ChatGPT, BERT, XLNet, Zhipu model, Claude, Moonshot AI model, ChatGLM model, Qianyi Tongwen model, MiniMax model, Spark model, Llama model, 360GPT model, Qwen model, Baichuan model, Skylark model, vivoLM model, and Wenxin Yiyan scale language models, which are not limited in the embodiments of the present application.

[0074] The embodiments of the present application provide a method, system, device, computer equipment and computer-readable storage medium for performance evaluation and analysis of air-ground game, which are described in detail below.

[0075] See also Figure 1 , Figure 1A schematic diagram of a scenario of an air-ground game performance evaluation and analysis system provided in an embodiment of the present application. The performance evaluation and analysis system may include a computer device 100, in which a performance evaluation and analysis system device for air-ground game is integrated, such as Figure 1 Computer equipment in.

[0076] In the embodiment of the present application, the computer device 100 may be an independent server, or a server network or server cluster composed of servers. For example, the computer device 100 described in the embodiment of the present application includes but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud server composed of a plurality of servers. The cloud server is composed of a large number of computers or network servers based on cloud computing.

[0077] It is understandable that the computer device 100 used in the embodiments of the present application may be a device including both receiving and transmitting hardware, that is, a device having receiving and transmitting hardware capable of performing two-way communication on a two-way communication link. Such a device may include: a cellular or other communication device having a single-line display or a multi-line display or a cellular or other communication device without a multi-line display. The specific computer device 100 may be a desktop terminal or a mobile terminal, and the computer device 100 may also be one of a mobile phone, a tablet computer, a laptop computer, etc.

[0078] Those skilled in the art will understand that Figure 1 The application environment shown in the figure is only one application scenario of the present application solution and does not constitute a limitation on the application scenario of the present application solution. Other application environments may also include Figure 1 More or less computer equipment as shown in Figure 1 Only one computer device is shown in the figure. It can be understood that the system can also include one or more other services, which are not limited here.

[0079] In addition, if Figure 1 As shown, the performance evaluation and analysis system for air-ground game may also include a memory 200 for storing simulation data, such as expert library data and simulation result data.

[0080] It should be noted that Figure 1The scenario diagram of the performance evaluation and analysis system for air-ground game shown is merely an example. The performance evaluation and analysis system for air-ground game and the scenario described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application. A person of ordinary skill in the art can appreciate that with the evolution of the simulation control management system and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is equally applicable to similar technical problems.

[0081] The present invention discloses a performance evaluation analysis method and system for air-ground game, which can flexibly select simulation result data according to user needs, and comprehensively use performance evaluation models and performance evaluation factor weights to evaluate the performance of air-ground game, thus meeting the urgent needs of air-ground game performance evaluation in complex environments. The following are detailed descriptions.

[0082] Embodiment 1

[0083] See also Figure 2 , Figure 2 : is a flow chart of a method for evaluating and analyzing the effectiveness of an air-ground game disclosed in an embodiment of the present invention. Figure 2 The described performance evaluation and analysis method for air-ground game is applied to a performance evaluation management system, such as a local server or a cloud server of the performance evaluation management system, and the embodiments of the present invention do not limit this. Figure 1 As shown, the performance evaluation and analysis method for the air-land game may include the following operations:

[0084] S1, determine the performance evaluation factors according to user needs and obtain simulation result data;

[0085] It should be noted that the determining of the performance evaluation factors according to the user's needs means that the user determines the performance evaluation indicator objects that need to be weighted according to the performance evaluation needs, and obtains the performance evaluation factors;

[0086] It should be noted that, in this embodiment, the effectiveness evaluation factors include, but are not limited to, damage effectiveness, survivability, economy and penetration capability;

[0087] It should be noted that the simulation result data is the simulation result data output by the simulation system of the previous level; the simulation result data includes but is not limited to the hit ratio, interception ratio, equipment quantity, equipment sortie, equipment ratio, equipment capability and equipment array ratio;

[0088] S2, processing the performance evaluation factors to obtain a performance evaluation factor weight matrix;

[0089] S3, based on the performance evaluation model, processing the performance evaluation factor weight matrix and the simulation result data to obtain a performance evaluation result;

[0090] It should be noted that the performance evaluation model is universal and can be modified and improved according to actual research needs.

[0091] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0092] In an optional embodiment, in the above step S2, the processing of the performance evaluation elements to obtain a performance evaluation element weight matrix includes:

[0093] S21, analyzing and processing the performance evaluation factors to obtain a set of indicators to be evaluated;

[0094] It should be noted that users can select performance evaluation factors according to their needs;

[0095] S22, using the weight determination model to process the parameter set of the indicator to be evaluated to obtain a first weight set;

[0096] S23, processing the set of indicators to be evaluated to obtain a first judgment matrix;

[0097] S24, using the first weight set, processing the first judgment matrix to obtain a second judgment matrix;

[0098] S25, performing characteristic vector calculation processing on the second judgment matrix to obtain a performance evaluation factor weight matrix.

[0099] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0100] In another optional embodiment, in the above step S21, analyzing and processing the performance evaluation elements to obtain a set of indicators to be evaluated includes:

[0101] S211, analyzing and processing the performance evaluation factors to obtain a target evaluation factor set;

[0102] For example, lethality, survivability, economy and penetration capability are used as the target evaluation factor set;

[0103] S212, analyzing and processing the target evaluation element set to obtain a set of indicators to be evaluated;

[0104] Exemplarily, the damage effectiveness is reflected by the hit ratio, the carrier survivability is reflected by the interception ratio, the economy is comprehensively reflected by the number of equipment and the number of aircraft sorties, and the penetration capability is comprehensively reflected by the equipment ratio, equipment capability and equipment array ratio. The hit ratio, the interception ratio, the equipment number, the equipment sorties, the equipment ratio, the equipment capability and the equipment array ratio are the set of indicators to be evaluated.

[0105] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0106] In another optional embodiment, in the above step S22, the weight determination model is used to process the parameter set of the indicator to be evaluated to obtain a first weight set, including:

[0107] S221, obtaining a parameter set of indicators to be evaluated;

[0108] The subjective and objective weighting method is used to obtain the subjective weight value set of the indicator parameter set to be evaluated;

[0109] S222, sorting the set of parameters of the indicator to be evaluated and the set of subjective weight values ​​of the indicator to obtain a data matrix;

[0110] S223, ranking the data matrix according to the importance of the evaluation index parameters to obtain an index rank value set;

[0111] The ranking process expression is:

[0112]

[0113] Among them, B i represents the rank value of the i-th indicator, i = 1, 2, 3…n; n represents the number of indicator parameters to be evaluated; h represents the number of subjective weight values ​​of the indicator; A ih represents the value of the element in the i-th row and h-th column of the data matrix; W h Indicates the subjective weight value of the hth indicator parameter to be evaluated;

[0114] S224, using an indicator weight calculation model, processing the indicator parameter set to be evaluated to obtain a first weight set;

[0115] The indicator weight calculation model expression is:

[0116]

[0117] Wherein, i represents the index of the parameter set to be evaluated, i=1, 2, 3…n; n represents the number of parameter sets to be evaluated; R i represents the i-th first weight value; W i represents the subjective weight value of the i-th indicator; B i represents the rank value of the i-th indicator;

[0118] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0119] In another optional embodiment, in the above step S23, the processing of the set of indicators to be evaluated to obtain a first judgment matrix includes:

[0120] S231, performing pairwise comparison and judgment on the set of indicators to be evaluated to obtain a preprocessing judgment result;

[0121] S232: Using a consistency judgment model, perform consistency check processing on the preprocessing judgment result to obtain a first judgment matrix.

[0122] It can be seen that the performance evaluation and analysis method and system for air-ground game described in the embodiment of the present invention can flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and performance evaluation factor weights to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0123] In an optional embodiment, in the above step S232, the consistency judgment model expression is:

[0124] A=(a ij ) n×n a ij >0,a ji =1 / a ij , i, j = 1, 2, ... n;

[0125] a ij =a ik a kj ,i,j,k=1,2,…,n;

[0126]

[0127] Among them, CR represents the consistency ratio; CI represents the consistency index; RI represents the average random consistency index; λ max represents the maximum characteristic root of A; A represents the first judgment matrix; a ij represents the scale of the i-th indicator to be evaluated with respect to the j-th indicator to be evaluated; a ji represents the scale of the jth indicator to be evaluated with respect to the ith indicator to be evaluated; a ik represents the scale of the i-th indicator to be evaluated with respect to the k-th indicator to be evaluated; a kj It represents the scale of the kth indicator to be evaluated with respect to the jth indicator to be evaluated; n represents the number of indicators to be evaluated.

[0128] It should be noted that, in this embodiment, the critical value of the consistency of the first judgment matrix is ​​0.1; the consistency ratio CR reflects the quality of the first judgment matrix. The smaller the CR, the higher the quality of the first judgment matrix; conversely, the more serious the logical conflict of the first judgment matrix, the lower the quality.

[0129] It should be noted that the size of RI is related to n, as shown in Table 1:

[0130] Table 1 Random consistency index table

[0131] Order n 1 2 3 5 6 7 8 9 RI 0.00 0.00 0.58 1.12 1.24 1.32 1.41 1.45

[0132] It can be seen that the performance evaluation and analysis method and system for air-ground game described in the embodiment of the present invention can flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and performance evaluation factor weights to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0133] In another optional embodiment, in the above step S231, performing pairwise comparison and judgment on the set of indicators to be evaluated to obtain a preprocessing judgment result includes:

[0134] S2311, traverse the set of indicators to be evaluated to obtain all indicators to be evaluated;

[0135] S2312, comparing and judging any two of the indicators to be evaluated to obtain a judgment result;

[0136] S2313, using a scaling method to quantize the judgment result to obtain a preprocessing judgment result;

[0137] It should be noted that this embodiment adopts a nine-scale method for quantization processing, and the meanings of each scale are shown in Table 2:

[0138] Table 2 Description of importance scale

[0139]

[0140] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0141] In another optional embodiment, in the above step S24, using the first weight set to process the first judgment matrix to obtain a second judgment matrix includes:

[0142] Using a second judgment matrix to obtain a model, the first weight set and the first judgment matrix are processed to obtain a comprehensive judgment matrix;

[0143] The second judgment matrix acquisition model expression is:

[0144]

[0145]

[0146] in, represents the second judgment matrix; represents the kth first judgment matrix; k represents the weight of the kth first judgment matrix, and λ k ≥0, m represents the number of the first judgment matrix.

[0147] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0148] In another optional embodiment, in the above step S3, the performance evaluation factor weight matrix and the simulation result data are processed based on the performance evaluation model to obtain the performance evaluation result, including:

[0149] S31, analyzing and processing the simulation result data to obtain first simulation result data, second simulation result data, third simulation result data, fourth simulation result data, fifth simulation result data, sixth simulation result data and seventh simulation result data;

[0150] It should be noted that the analysis process refers to extracting simulation result data according to the data type identifier;

[0151] Exemplarily, taking the air-ground game simulation result data as an example, in this embodiment, the first simulation result data refers to the hit ratio; the second simulation result data refers to the interception ratio; the third simulation result data refers to the number of equipment; the fourth simulation result data refers to the equipment sorties; the fifth simulation result data refers to the equipment ratio; the sixth simulation result data refers to the equipment capability; the seventh simulation result data refers to the equipment array ratio;

[0152] S32, processing the performance evaluation factor weight matrix to obtain a first weight value, a second weight value, a third weight value, a fourth weight value, a fifth weight value, a sixth weight value, a seventh weight value and an eighth weight value;

[0153] It should be noted that, in this embodiment, the first weight value is 0.5; the second weight value is 0.5; the third weight value is 0.3; the fourth weight value is 0.3; the fifth weight value is 0.5; the sixth weight value is 0.2; the seventh weight value is 0.1; the eighth weight value is 0.7;

[0154] S33, based on the performance evaluation model, the first simulation result data, the second simulation result data, the third simulation result data, the fourth simulation result data, the fifth simulation result data, the sixth simulation result data, the seventh simulation result data, the first weight value, the second weight value, the third weight value, the fourth weight value, the fifth weight value, the sixth weight value, the seventh weight value and the eighth weight value are processed to obtain a performance evaluation result.

[0155] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0156] In another optional embodiment, in the above step S33, based on the performance evaluation model, the first simulation result data, the second simulation result data, the third simulation result data, the fourth simulation result data, the fifth simulation result data, the sixth simulation result data, the seventh simulation result data, the first weight value, the second weight value, the third weight value, the fourth weight value, the fifth weight value, the sixth weight value, the seventh weight value and the eighth weight value are processed to obtain a performance evaluation result, including:

[0157] S331, acquiring first performance evaluation information based on the first simulation result data;

[0158] It should be noted that the data information directly extracted from the first simulation result data is the first performance evaluation information;

[0159] Based on the second simulation result data, obtaining second performance evaluation information;

[0160] It should be noted that the data information directly extracted from the second simulation result data is the second performance evaluation information;

[0161] Processing the third simulation result data and the first weight value to obtain third performance evaluation information;

[0162] It should be noted that the processing of the third simulation result data and the first weight value to obtain the third performance evaluation information means multiplying the third simulation result data and the first weight value to obtain the third performance evaluation information;

[0163] Processing the fourth simulation result data and the second weight value to obtain fourth performance evaluation information;

[0164] It should be noted that the processing of the fourth simulation result data and the second weight value to obtain the fourth performance evaluation information means multiplying the fourth simulation result data and the second weight value to obtain the fourth performance evaluation information;

[0165] Processing the fifth simulation result data and the third weight value to obtain fifth performance evaluation information;

[0166] It should be noted that the fifth simulation result data and the third weight value are processed to obtain the fifth performance evaluation information, which means that the fifth simulation result data and the third weight value are multiplied to obtain the fifth performance evaluation information;

[0167] Processing the sixth simulation result data and the fourth weight value to obtain sixth performance evaluation information;

[0168] It should be noted that the processing of the sixth simulation result data and the fourth weight value to obtain the sixth performance evaluation information means multiplying the sixth simulation result data and the fourth weight value to obtain the sixth performance evaluation information;

[0169] Processing the seventh simulation result data and the fifth weight value to obtain seventh performance evaluation information;

[0170] It should be noted that the seventh simulation result data and the fifth weight value are processed to obtain the seventh performance evaluation information, which means that the seventh simulation result data and the fifth weight value are processed to obtain the seventh performance evaluation information;

[0171] S332, processing the third performance evaluation information and the fourth performance evaluation information to obtain eighth performance evaluation information;

[0172] It should be noted that the third performance evaluation information and the fourth performance evaluation information are processed to obtain the eighth performance evaluation information, indicating

[0173] Processing the fifth performance evaluation information, the sixth performance evaluation information, and the seventh performance evaluation information to obtain ninth performance evaluation information;

[0174] It should be noted that the fifth performance evaluation information, the sixth performance evaluation information and the seventh performance evaluation information are processed to obtain the ninth performance evaluation information, indicating that

[0175] S333, processing the second performance evaluation information and the sixth weight value to obtain tenth performance evaluation information;

[0176] It should be noted that the processing of the second performance evaluation information and the sixth weight value to obtain the tenth performance evaluation information means multiplying the second performance evaluation information and the sixth weight value to obtain the tenth performance evaluation information;

[0177] Processing the third performance evaluation information and the fourth performance evaluation information to obtain eleventh performance evaluation information;

[0178] It should be noted that the processing of the third performance evaluation information and the fourth performance evaluation information to obtain the eleventh performance evaluation information means performing a summation and multiplication process on the third performance evaluation information and the fourth performance evaluation information to obtain the eleventh performance evaluation information;

[0179] Processing the fifth performance evaluation information, the sixth performance evaluation information, and the seventh performance evaluation information to obtain twelfth performance evaluation information;

[0180] It should be noted that the processing of the fifth performance evaluation information, the sixth performance evaluation information and the seventh performance evaluation information to obtain the twelfth performance evaluation information means that the fifth performance evaluation information, the sixth performance evaluation information and the seventh performance evaluation information are summed and multiplied to obtain the twelfth performance evaluation information;

[0181] S334, processing the tenth performance evaluation information, the eleventh performance evaluation information and the twelfth performance evaluation information to obtain comprehensive performance evaluation information;

[0182] It should be noted that the processing of the tenth performance evaluation information, the eleventh performance evaluation information and the twelfth performance evaluation information to obtain the comprehensive performance evaluation information means that the tenth performance evaluation information, the eleventh performance evaluation information and the twelfth performance evaluation information are summed and multiplied to obtain the comprehensive performance evaluation information;

[0183] S335, multiplying the first performance evaluation information and the comprehensive performance evaluation information to obtain a performance evaluation result.

[0184] It can be seen that the performance evaluation and analysis method for air-ground game described in the embodiment of the present invention can be implemented to flexibly select simulation result data according to user needs, and comprehensively use the performance evaluation model and the weights of performance evaluation factors to evaluate the performance of air-ground game, thereby meeting the urgent needs of air-ground game performance evaluation in complex environments.

[0185] Embodiment 2

[0186] See also Figure 3 , Figure 3 Schematic diagram of the structure of a performance evaluation and analysis system for air-ground game disclosed in an embodiment of the present invention. Figure 3 The described system can be applied to the performance evaluation and analysis management system for air-ground games, such as a local server or cloud server for analyzing and evaluating the control system, and the embodiments of the present invention are not limited thereto. Figure 3 As shown, the system may include:

[0187] Data acquisition module 101, first processing module 102 and second processing module 103;

[0188] The data acquisition module 101 is used to determine the performance evaluation factors according to user needs and obtain simulation result data;

[0189] The first processing module 102 is used to process the performance evaluation elements to obtain a performance evaluation element weight matrix;

[0190] The second processing module 103 is used to process the performance evaluation factor weight matrix and the simulation result data based on the performance evaluation model to obtain a performance evaluation result.

[0191] Embodiment 3

[0192] See also Figure 4 , Figure 4Schematic diagram of the structure of a performance evaluation and analysis device for air-ground game disclosed in an embodiment of the present invention. Figure 4 The described device can be applied to the performance evaluation and analysis management system for air-ground games, such as a local server or cloud server for analyzing and evaluating the control system, and the embodiments of the present invention are not limited thereto. Figure 4 As shown, the device may include:

[0193] A memory 201 storing executable program codes;

[0194] a processor 202 coupled to the memory 201;

[0195] The processor 202 calls the executable program code stored in the memory 201 to execute the steps in the performance evaluation and analysis method for the space-land game described in the first embodiment.

[0196] Embodiment 4

[0197] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the performance evaluation and analysis method for space-land game described in the first embodiment.

[0198] Embodiment 5

[0199] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the performance evaluation and analysis method for space-land game described in the first embodiment.

[0200] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0201] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, a magnetic disk storage, a magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0202] Finally, it should be noted that the performance evaluation and analysis method, system and device for air-ground game disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, which are only used to illustrate the technical scheme of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical schemes described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical schemes from the spirit and scope of the technical schemes of the embodiments of the present invention.

Claims

1. A performance evaluation and analysis method for space-land game, characterized in that: The method comprises: S1, determine the performance evaluation factors according to user needs and obtain simulation result data; S2, processing the performance evaluation factors to obtain a performance evaluation factor weight matrix; S3, based on the performance evaluation model, processing the performance evaluation factor weight matrix and the simulation result data to obtain a performance evaluation result.

2. The performance evaluation and analysis method for space-land game according to claim 1 is characterized in that: The processing of the performance evaluation elements to obtain a performance evaluation element weight matrix includes: S21, analyzing and processing the performance evaluation factors to obtain a set of indicators to be evaluated; S22, using the weight determination model to process the parameter set of the indicator to be evaluated to obtain a first weight set; S23, processing the set of indicators to be evaluated to obtain a first judgment matrix; S24, using the first weight set, processing the first judgment matrix to obtain a second judgment matrix; S25, performing characteristic vector calculation processing on the second judgment matrix to obtain a performance evaluation factor weight matrix.

3. The performance evaluation and analysis method for space-land game according to claim 2 is characterized in that: The step of processing the set of indicators to be evaluated to obtain a first judgment matrix includes: S231, performing pairwise comparison and judgment on the set of indicators to be evaluated to obtain a preprocessing judgment result; S232: Using a consistency judgment model, perform consistency check processing on the pre-processing judgment result to obtain a first judgment matrix.

4. The performance evaluation and analysis method for space-land game according to claim 3 is characterized in that: The consistency judgment model expression is: A=(a ij ) n×n a ij >0,a ji =1 / a ij ,i,j=1,2,…n; a ij =a ik a kj ,i,j,k=1,2,...,n; Among them, CR represents the consistency ratio; CI represents the consistency index; RI represents the average random consistency index; λ max represents the maximum characteristic root of A; A represents the first judgment matrix; a ij represents the scale of the i-th indicator to be evaluated with respect to the j-th indicator to be evaluated; a ji represents the scale of the jth indicator to be evaluated with respect to the ith indicator to be evaluated; a ik represents the scale of the i-th indicator to be evaluated with respect to the k-th indicator to be evaluated; a kj It represents the scale of the kth indicator to be evaluated with respect to the jth indicator to be evaluated; n represents the number of indicators to be evaluated.

5. The performance evaluation and analysis method for space-land game according to claim 2 is characterized in that: The using the first weight set to process the first judgment matrix to obtain a second judgment matrix includes: Using the second judgment matrix to obtain a model, the first weight set and the first judgment matrix are processed to obtain a comprehensive judgment matrix; The second judgment matrix acquisition model expression is: in, represents the second judgment matrix; represents the kth first judgment matrix; k represents the weight of the kth first judgment matrix, and λ k ≥0, m represents the number of the first judgment matrix.

6. The performance evaluation and analysis method for space-land game according to claim 1 is characterized in that: The performance evaluation model is based on which the performance evaluation factor weight matrix and the simulation result data are processed to obtain a performance evaluation result, including: S31, analyzing and processing the simulation result data to obtain first simulation result data, second simulation result data, third simulation result data, fourth simulation result data, fifth simulation result data, sixth simulation result data and seventh simulation result data; S32, processing the performance evaluation factor weight matrix to obtain a first weight value, a second weight value, a third weight value, a fourth weight value, a fifth weight value, a sixth weight value, a seventh weight value and an eighth weight value; S33, based on the performance evaluation model, the first simulation result data, the second simulation result data, the third simulation result data, the fourth simulation result data, the fifth simulation result data, the sixth simulation result data, the seventh simulation result data, the first weight value, the second weight value, the third weight value, the fourth weight value, the fifth weight value, the sixth weight value, the seventh weight value and the eighth weight value are processed to obtain a performance evaluation result.

7. The performance evaluation and analysis method for space-land game according to claim 6 is characterized in that: The first simulation result data, the second simulation result data, the third simulation result data, the fourth simulation result data, the fifth simulation result data, the sixth simulation result data, the seventh simulation result data, the first weight value, the second weight value, the third weight value, the fourth weight value, the fifth weight value, the sixth weight value, the seventh weight value and the eighth weight value are processed based on the performance evaluation model to obtain a performance evaluation result, including: S331, acquiring first performance evaluation information based on the first simulation result data; Based on the second simulation result data, obtaining second performance evaluation information; Processing the third simulation result data and the first weight value to obtain third performance evaluation information; Processing the fourth simulation result data and the second weight value to obtain fourth performance evaluation information; Processing the fifth simulation result data and the third weight value to obtain fifth performance evaluation information; Processing the sixth simulation result data and the fourth weight value to obtain sixth performance evaluation information; Processing the seventh simulation result data and the fifth weight value to obtain seventh performance evaluation information; S332, processing the third performance evaluation information and the fourth performance evaluation information to obtain eighth performance evaluation information; Processing the fifth performance evaluation information, the sixth performance evaluation information, and the seventh performance evaluation information to obtain ninth performance evaluation information; S333, processing the second performance evaluation information and the sixth weight value to obtain tenth performance evaluation information; Processing the third performance evaluation information and the fourth performance evaluation information to obtain eleventh performance evaluation information; Processing the fifth performance evaluation information, the sixth performance evaluation information, and the seventh performance evaluation information to obtain twelfth performance evaluation information; S334, processing the tenth performance evaluation information, the eleventh performance evaluation information and the twelfth performance evaluation information to obtain comprehensive performance evaluation information; S335, multiplying the first performance evaluation information and the comprehensive performance evaluation information to obtain a performance evaluation result.

8. A performance evaluation and analysis system for air-ground game, characterized in that: The system comprises: A data acquisition module, a first processing module and a second processing module; The data acquisition module is used to determine the performance evaluation factors according to user needs and obtain simulation result data; The first processing module is used to process the performance evaluation elements to obtain a performance evaluation element weight matrix; The second processing module is used to process the performance evaluation factor weight matrix and the simulation result data based on the performance evaluation model to obtain a performance evaluation result.

9. A performance evaluation and analysis device for air-ground game, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the performance evaluation and analysis method for air-ground game as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the performance evaluation and analysis method for space-land game as described in any one of claims 1-7.

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