A method and system for evaluating the effectiveness of a police reconnaissance cloud platform system

Abstract

The present invention discloses a police reconnaissance cloud platform system performance evaluation method and system, including: using the analytic hierarchy process to establish a performance evaluation index system for the police reconnaissance cloud platform system; collecting the values ​​of each performance evaluation index of each evaluation object to obtain a performance evaluation matrix, normalizing the performance evaluation matrix to obtain a normalized performance evaluation matrix; using an objective weighting method to calculate the weight assignment of each performance evaluation index of any evaluation object in the normalized performance evaluation matrix, using the TOPSIS method to calculate and obtain the distance from the performance of any evaluation object to the positive and negative ideal solutions, and calculating it to obtain the performance evaluation value of any evaluation object; sorting the performance evaluation values ​​of all evaluation objects to obtain the performance evaluation result of the police reconnaissance cloud platform system. The present invention solves the problem that the performance evaluation of the police reconnaissance cloud platform system relies on subjective judgment and lacks a scientific and reasonable quantitative evaluation method.

Description

Technical Field

[0001] The present invention belongs to the field of police reconnaissance technology, and more specifically, relates to a method and system for evaluating the effectiveness of a police reconnaissance cloud platform system. Background Art

[0002] With the gradual improvement of informatization construction, the police reconnaissance cloud platform system, as an important part of the command and reconnaissance system, plays a vital role in multi-source information fusion, heterogeneous data analysis, and action decision-making in restricted areas.

[0003] System effectiveness reflects the system's ability to perceive, extract features, analyze status, and deploy actions for audio and video images of pedestrians and vehicles, as well as the effectiveness of task completion. In general, the research and development of the police reconnaissance cloud platform system has achieved phased results. However, the current evaluation of the effectiveness of the police reconnaissance cloud platform system only relies on the subjective qualitative description of police staff, and lacks a scientific and reasonable quantitative evaluation system.

[0004] The analytic hierarchy process is a systematic and hierarchical analysis method that combines qualitative and quantitative methods. The characteristic of this method is that it uses less quantitative information to make the decision-making thinking process mathematical based on in-depth research on the nature, influencing factors and their internal relationships of complex decision-making problems, thereby providing a simple decision-making method for complex decision-making problems with multiple objectives, multiple criteria or unstructured characteristics.

[0005] Objective weighting method is a means to define and evaluate the competitiveness of an enterprise. The weights are determined by certain mathematical methods based on the relationship between the original data. The judgment results do not depend on human subjective judgment and have a strong mathematical theoretical basis. Commonly used objective weighting methods usually include principal component analysis, deviation and mean square error method, multi-objective planning method, etc.

[0006] The TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method was first proposed by CL Hwang and K. Yoon in 1981. It is known as the ideal solution approximation method in China. The TOPSIS method is a method of ranking a finite number of evaluation objects according to their proximity to an idealized target. It is a relative evaluation of existing objects.

[0007] In summary, although the existing technology can solve the performance evaluation of the police reconnaissance cloud platform system, it relies on manual subjective judgment of the performance evaluation results. Therefore, providing a multi-level, structured performance evaluation model to objectively and quantitatively evaluate the system performance is an urgent problem to be solved. Summary of the invention

[0008] In view of the defects of the prior art, the present invention provides a method and system for evaluating the effectiveness of a police reconnaissance cloud platform system, which solves the technical problem that the prior art relies on manual judgment of the effectiveness of the police reconnaissance cloud platform system and lacks scientific and reasonable quantitative evaluation.

[0009] To achieve the above object, the present invention provides a method for evaluating the effectiveness of a police reconnaissance cloud platform system, comprising the following steps:

[0010] (1) Steps for establishing the effectiveness evaluation system: Based on the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established using the hierarchical analysis method;

[0011] (2) Steps for constructing an effectiveness evaluation matrix: According to the effectiveness evaluation index system of the police reconnaissance cloud platform system, the values ​​of each effectiveness evaluation index of each evaluation object are collected to obtain an effectiveness evaluation matrix, and the values ​​of each effectiveness evaluation index of each evaluation object in the effectiveness evaluation matrix are normalized to obtain a normalized effectiveness evaluation matrix;

[0012] (3) Obtaining the performance evaluation value of any evaluation object: using an objective weighting method to calculate the weight assignment of each performance evaluation indicator of any evaluation object in the normalized performance evaluation matrix, using the TOPSIS method to calculate and obtain the distance from the performance of any evaluation object to the positive and negative ideal solutions based on the weight assignment of each performance evaluation indicator of any evaluation object and the maximum and minimum values ​​of each performance evaluation indicator in all evaluation objects, and obtaining the performance evaluation value of any evaluation object based on the distance from the performance of any evaluation object to the positive and negative ideal solutions;

[0013] (4) Steps for obtaining performance evaluation results: Sort the performance evaluation values ​​of all evaluation objects to obtain the performance evaluation results of the police reconnaissance cloud platform system.

[0014] In an optional embodiment, in the step of establishing the effectiveness evaluation system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established by using the hierarchical analysis method, specifically:

[0015] According to the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation indicators of the police reconnaissance cloud platform system are divided into several first-level indicators at the criterion level and second-level indicators at the execution level;

[0016] Among them, the first-level indicators of the criterion layer include: information perception capability, feature analysis capability, and action decision-making capability; the information perception capability also includes the following second-level indicators of the execution layer: facial attribute perception capability, behavioral attribute perception capability, motor vehicle attribute perception capability, and non-motor vehicle attribute perception capability; the feature analysis capability also includes the following second-level indicators of the execution layer: recognition accuracy and effective alarm rate; the action decision-making capability also includes the following second-level indicators of the execution layer: timeliness of intelligence processing, rationality of personnel allocation, and effective utilization of equipment.

[0017] In an optional embodiment, the execution layer secondary indicator further includes:

[0018] The secondary indicators of the execution layer can be divided into benefit indicators and cost indicators according to different attributes; among them, benefit indicators include: facial attribute perception ability, behavioral attribute perception ability, motor vehicle attribute perception ability, non-motor vehicle attribute perception ability, rationality of personnel allocation, and effective utilization rate of equipment; cost indicators include: recognition accuracy, effective alarm rate, and timeliness of intelligence processing.

[0019] In an optional embodiment, in the step of constructing the performance evaluation matrix, the value of each performance evaluation index of each evaluation object in the performance evaluation matrix is ​​normalized, specifically:

[0020] If the performance evaluation index is a benefit-type index, the normalization processing method of the performance evaluation index of each evaluation object is: subtract the value of the performance evaluation index of each evaluation object from the minimum value of the performance evaluation index of all evaluation objects, and divide the obtained difference by the difference between the maximum value and the minimum value of the performance evaluation index of all evaluation objects;

[0021] If the performance evaluation indicator is a cost-type indicator, the normalization method of the performance evaluation indicator of each evaluation object is: subtract the value of the performance evaluation indicator of each evaluation object from the maximum value of the performance evaluation indicator in all evaluation objects, and divide the obtained difference by the difference between the maximum value and the minimum value of the performance evaluation indicator in all evaluation objects.

[0022] In an optional embodiment, in the step of obtaining the performance evaluation value of any evaluation object, an objective weighting method is used to calculate the weight assignment of each performance evaluation index of any evaluation object in the normalized performance evaluation matrix, specifically:

[0023] Calculate the standard deviation and conflict quantization value of each performance evaluation indicator of any evaluation object in the normalized performance evaluation matrix, calculate the standard deviation and conflict quantization value of each performance evaluation indicator, obtain the information amount of each performance evaluation indicator, calculate the information amount of each performance evaluation indicator, and obtain the weight assignment of each performance evaluation indicator of any evaluation object.

[0024] In an optional embodiment, in the step of obtaining the performance evaluation value of each evaluation object, the performance evaluation value of any evaluation object is obtained according to the distance from the performance of any evaluation object to the positive and negative ideal solutions, specifically:

[0025] The distance from the performance of any evaluation object to the negative ideal solution is divided by the sum of the distances from the performance of any evaluation object to the positive and negative ideal solutions to obtain the performance evaluation value of any evaluation object.

[0026] On the other hand, the present invention also provides an effectiveness evaluation system for a police reconnaissance cloud platform system, comprising the following units:

[0027] Establishing the effectiveness evaluation system unit: Based on the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established using the hierarchical analysis method;

[0028] Constructing the effectiveness evaluation matrix unit: according to the effectiveness evaluation index system of the police reconnaissance cloud platform system, collecting the values ​​of each effectiveness evaluation index of each evaluation object to obtain the effectiveness evaluation matrix, normalizing the values ​​of each effectiveness evaluation index of each evaluation object in the effectiveness evaluation matrix to obtain the normalized effectiveness evaluation matrix;

[0029] Obtaining the performance evaluation value unit of any evaluation object: using the objective weighting method to calculate the weight assignment of each performance evaluation index of any evaluation object in the normalized performance evaluation matrix, using the TOPSIS method to calculate and obtain the distance from the performance of any evaluation object to the positive and negative ideal solutions according to the weight assignment of each performance evaluation index of any evaluation object and the maximum and minimum values ​​of each performance evaluation index in all evaluation objects, and obtaining the performance evaluation value of any evaluation object according to the distance from the performance of any evaluation object to the positive and negative ideal solutions;

[0030] Obtaining performance evaluation result unit: sorting the performance evaluation values ​​of all evaluation objects to obtain the performance evaluation result of the police reconnaissance cloud platform system.

[0031] In general, the above technical solution conceived by the present invention has the following beneficial effects compared with the prior art:

[0032] The present invention provides a method and system for evaluating the effectiveness of a police reconnaissance cloud platform system. The effectiveness evaluation index system of the police reconnaissance cloud platform system is established by the hierarchical analysis method, and the weight assignment of each effectiveness evaluation index in the effectiveness evaluation matrix is ​​obtained by the objective weighting method. Finally, the TOPSIS method is used to calculate the distance between the effectiveness of each evaluation object and the positive ideal solution and the negative ideal solution. The effectiveness of each evaluation object is sorted by the distance between the effectiveness of the evaluation object and the positive ideal solution and the negative ideal solution, and the effectiveness evaluation result of the police reconnaissance cloud platform system is obtained.

[0033] The present invention solves the problem that the police reconnaissance cloud platform system has long relied on manual judgment for performance evaluation and lacks a scientific and reasonable quantitative evaluation method, thereby improving the efficiency and accuracy of the police reconnaissance cloud platform system performance evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flow chart of the performance evaluation method of the police reconnaissance cloud platform system of the present invention;

[0035] Figure 2 It is a framework diagram of the system performance evaluation index system of the police reconnaissance cloud platform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0037] like Figure 1 As shown, the effectiveness evaluation method of the police reconnaissance cloud platform system of the present invention comprises the following steps:

[0038] (1) Steps for establishing the effectiveness evaluation system: Based on the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established using the hierarchical analysis method;

[0039] (2) Steps for constructing an effectiveness evaluation matrix: According to the effectiveness evaluation index system of the police reconnaissance cloud platform system, the values ​​of each effectiveness evaluation index of each evaluation object are collected to obtain an effectiveness evaluation matrix, and the values ​​of each effectiveness evaluation index of each evaluation object in the effectiveness evaluation matrix are normalized to obtain a normalized effectiveness evaluation matrix;

[0040] (3) Obtaining the performance evaluation value of any evaluation object: using an objective weighting method to calculate the weight assignment of each performance evaluation indicator of any evaluation object in the normalized performance evaluation matrix, using the TOPSIS method to calculate and obtain the distance from the performance of any evaluation object to the positive and negative ideal solutions based on the weight assignment of each performance evaluation indicator of any evaluation object and the maximum and minimum values ​​of each performance evaluation indicator in all evaluation objects, and obtaining the performance evaluation value of any evaluation object based on the distance from the performance of any evaluation object to the positive and negative ideal solutions;

[0041] (4) Steps for obtaining performance evaluation results: Sort the performance evaluation values ​​of all evaluation objects to obtain the performance evaluation results of the police reconnaissance cloud platform system.

[0042] Specifically, the effectiveness evaluation method of the police reconnaissance cloud platform system provided by the embodiment of the present invention is as follows:

[0043] (1) Steps for establishing a performance evaluation system.

[0044] The system performance evaluation index system of the police reconnaissance cloud platform according to the embodiment of the present invention is as follows: Figure 2 As shown, the first-level indicators of the criterion layer include: information perception ability, feature analysis ability, and action decision-making ability;

[0045] Each first-level indicator of the criterion layer includes several second-level indicators of the execution layer. Among them, the information perception capability includes the following second-level indicators of the execution layer: facial attribute perception capability, behavioral attribute perception capability, motor vehicle attribute perception capability, and non-motor vehicle attribute perception capability; the feature analysis capability includes the following second-level indicators of the execution layer: recognition accuracy rate and effective alarm rate; the action decision-making capability includes the following second-level indicators of the execution layer: intelligence processing timeliness, rationality of personnel allocation, and effective utilization rate of equipment.

[0046] Among them, the secondary indicators of the execution layer can be divided into benefit-type indicators and cost-type indicators. For benefit-type indicators, the numerical value is positively correlated with the performance evaluation results; for cost-type indicators, the numerical value is negatively correlated with the performance evaluation results.

[0047] In the actual system data collection, for the information perception capability, we use artificial intelligence recognition algorithms to capture the attribute features of faces, behaviors, motor vehicles, and non-motor vehicles. The number of perceived and recognized attribute feature data in 100 sets is used as the basis for evaluating the information perception capability. Therefore, the four indicators under the information perception capability are all benefit-oriented indicators.

[0048] For the recognition accuracy and effective alarm rate in the feature analysis capability, the number of false recognitions and the number of invalid alarms are used as the evaluation basis. The fewer the number of false recognitions, the higher the recognition accuracy, and the fewer the number of invalid alarms, the higher the effective alarm rate. Therefore, the recognition accuracy and effective alarm rate under the feature analysis capability are both cost-based indicators;

[0049] The timeliness of intelligence processing refers to the time from "intelligence acquisition" to "action decision making". The shorter this time is, the higher the timeliness is. Therefore, it is a cost-type indicator. Personnel rationality and equipment utilization are obtained through expert evaluation and are benefit-type indicators.

[0050] (2) Steps to construct an effectiveness evaluation matrix.

[0051] In the embodiment of the present invention, the number of evaluation objects is 5, and 9 execution layer secondary indicators are used as performance evaluation indicators of the police reconnaissance cloud platform system to obtain the performance evaluation matrix U.

[0052]

[0053] r ij Represents the value of the jth performance evaluation index corresponding to the i-th evaluation object in the performance evaluation matrix. Among them, 1≤i≤5, 1≤j≤9.

[0054] Use normalization method to process benefit-type indicators and cost-type indicators in the performance evaluation matrix.

[0055] If r ijIt is a benefit indicator, and the normalized processing formula is as follows:

[0056]

[0057] Among them, r jmax Represents the maximum value of the jth performance evaluation index among all evaluation objects, r jmin Represents the minimum value of the jth performance evaluation index among all evaluation objects.

[0058] If r ij It is a cost-based indicator, and the normalized processing formula is as follows:

[0059]

[0060] The values ​​of each performance evaluation index of each evaluation object in the performance evaluation matrix are normalized using the above formula, and the normalized performance evaluation matrix U′ is obtained as follows:

[0061]

[0062] (3) A step of obtaining the performance evaluation value of any evaluation object.

[0063] (3.1) The objective weighting method is used to obtain the weight assignment of each performance evaluation indicator of any evaluation object in the performance evaluation matrix.

[0064] Calculate the normalized performance evaluation matrix U′ and calculate the average value of each performance evaluation index. Taking the performance evaluation index of the jth column as an example, the calculation formula is as follows:

[0065]

[0066] Among them, U j Represents the average value of the performance evaluation index in the jth column.

[0067] Calculate the standard deviation σ of the performance evaluation index in the jth column j :

[0068]

[0069] Calculate the conflict quantification value P of each performance evaluation index j :

[0070]

[0071] Where k represents the kth of the 9 performance evaluation indicators, where 1≤k≤9; r jk Represents the kth performance evaluation indicator of the jth evaluation object.

[0072] Calculate the amount of information Q contained in the jth performance evaluation indexj :

[0073] Q j =σ j ×P j

[0074] The weight assignment W of the jth performance evaluation index j :

[0075]

[0076] (3.2) Calculate the distance from the effectiveness of any evaluation object to the positive and negative ideal solutions, and obtain the effectiveness evaluation value of any evaluation object.

[0077] The TOPSIS method is used to calculate the distance between the performance of each evaluation object and the positive and negative ideal solutions. The distance between the performance of the i-th evaluation object and the positive ideal solution The calculation formula is as follows:

[0078]

[0079] The distance from the performance of the i-th evaluation object to the negative ideal solution The calculation formula is as follows:

[0080]

[0081] The performance evaluation value C of the i-th evaluation object i The calculation formula is as follows:

[0082]

[0083] Use the above formula to calculate the efficacy evaluation value of each evaluation object.

[0084] (4) Steps for obtaining performance evaluation results.

[0085] The obtained performance evaluation values ​​of each evaluation object are sorted from small to large to obtain the performance evaluation result of the police reconnaissance cloud platform system.

[0086] Specifically, the effectiveness evaluation system of the police reconnaissance cloud platform system provided by the embodiment of the present invention includes the following units:

[0087] Establishing the effectiveness evaluation system unit: Based on the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established using the hierarchical analysis method;

[0088] Constructing the effectiveness evaluation matrix unit: according to the effectiveness evaluation index system of the police reconnaissance cloud platform system, collecting the values ​​of each effectiveness evaluation index of each evaluation object to obtain the effectiveness evaluation matrix, normalizing the values ​​of each effectiveness evaluation index of each evaluation object in the effectiveness evaluation matrix to obtain the normalized effectiveness evaluation matrix;

[0089] Obtaining the performance evaluation value unit of any evaluation object: using the objective weighting method to calculate the weight assignment of each performance evaluation index of any evaluation object in the normalized performance evaluation matrix, using the TOPSIS method to calculate and obtain the distance from the performance of any evaluation object to the positive and negative ideal solutions according to the weight assignment of each performance evaluation index of any evaluation object and the maximum and minimum values ​​of each performance evaluation index in all evaluation objects, and obtaining the performance evaluation value of any evaluation object according to the distance from the performance of any evaluation object to the positive and negative ideal solutions;

[0090] Obtaining performance evaluation result unit: sorting the performance evaluation values ​​of all evaluation objects to obtain the performance evaluation result of the police reconnaissance cloud platform system.

[0091] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the effectiveness of a police reconnaissance cloud platform system, characterized in that: The steps include: (1) Steps for establishing the effectiveness evaluation system: Based on the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established using the hierarchical analysis method; (2) Steps for constructing an effectiveness evaluation matrix: According to the effectiveness evaluation index system of the police reconnaissance cloud platform system, the values ​​of each effectiveness evaluation index of each evaluation object are collected to obtain an effectiveness evaluation matrix, and the values ​​of each effectiveness evaluation index of each evaluation object in the effectiveness evaluation matrix are normalized to obtain a normalized effectiveness evaluation matrix; (3) Obtaining the performance evaluation value of any evaluation object: using an objective weighting method to calculate the weight assignment of each performance evaluation indicator of any evaluation object in the normalized performance evaluation matrix, using the TOPSIS method to calculate and obtain the distance from the performance of any evaluation object to the positive and negative ideal solutions based on the weight assignment of each performance evaluation indicator of any evaluation object and the maximum and minimum values ​​of each performance evaluation indicator in all evaluation objects, and obtaining the performance evaluation value of any evaluation object based on the distance from the performance of any evaluation object to the positive and negative ideal solutions; (4) Obtaining the effectiveness evaluation result step: sorting the effectiveness evaluation values ​​of all evaluation objects to obtain the effectiveness evaluation result of the police reconnaissance cloud platform system; In the step of establishing the effectiveness evaluation system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established by using the hierarchical analysis method, specifically: According to the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation indicators of the police reconnaissance cloud platform system are divided into several first-level indicators at the criterion level and second-level indicators at the execution level; Among them, the first-level indicators of the criterion layer include: information perception ability, feature analysis ability, and action decision-making ability; the information perception ability also includes the following second-level indicators of the execution layer: facial attribute perception ability, behavioral attribute perception ability, motor vehicle attribute perception ability, and non-motor vehicle attribute perception ability; the feature analysis ability also includes the following second-level indicators of the execution layer: recognition accuracy rate and effective alarm rate; the action decision-making ability also includes the following second-level indicators of the execution layer: intelligence processing timeliness, rationality of personnel allocation, and effective utilization rate of equipment; The execution layer secondary indicators also include: The secondary indicators of the execution layer can be divided into benefit indicators and cost indicators according to different attributes; among them, benefit indicators include: facial attribute perception ability, behavioral attribute perception ability, motor vehicle attribute perception ability, non-motor vehicle attribute perception ability, rationality of personnel allocation, and effective utilization rate of equipment; cost indicators include: recognition accuracy, effective alarm rate, and timeliness of intelligence processing; The method for obtaining the benefit-based indicator includes: Through artificial intelligence recognition algorithms, the attributes of faces, behaviors, motor vehicles and non-motor vehicles are captured, and the number of target attribute feature data that can be perceived and recognized is used as the basis for evaluating information perception capabilities to achieve information perception; Determine the rationality of personnel allocation and effective utilization of equipment through expert evaluation; The method for obtaining the cost-based indicator includes: Obtain the number of false recognitions and the number of invalid alarms, determine the false recognition rate according to the number of false recognitions, and determine the valid alarm rate according to the number of invalid alarms; The timeliness of intelligence processing is determined based on the time of intelligence acquisition and the time of action strategy formulation. The shorter the intelligence processing timeliness is, the higher the timeliness is.

2. The method for evaluating the effectiveness of a police reconnaissance cloud platform system according to claim 1, characterized in that: In the step of constructing the performance evaluation matrix, the values ​​of each performance evaluation index of each evaluation object in the performance evaluation matrix are normalized, specifically: If the performance evaluation index is a benefit-type index, the normalization processing method of the performance evaluation index of each evaluation object is: subtract the value of the performance evaluation index of each evaluation object from the minimum value of the performance evaluation index of all evaluation objects, and divide the obtained difference by the difference between the maximum value and the minimum value of the performance evaluation index of all evaluation objects; If the performance evaluation indicator is a cost-type indicator, the normalization method of the performance evaluation indicator of each evaluation object is: subtract the value of the performance evaluation indicator of each evaluation object from the maximum value of the performance evaluation indicator in all evaluation objects, and divide the obtained difference by the difference between the maximum value and the minimum value of the performance evaluation indicator in all evaluation objects.

3. The method for evaluating the effectiveness of a police reconnaissance cloud platform system according to claim 1, characterized in that: In the step of obtaining the performance evaluation value of any evaluation object, the objective weighting method is used to calculate the weight assignment of each performance evaluation index of any evaluation object in the normalized performance evaluation matrix, specifically: Calculate the standard deviation and conflict quantization value of each performance evaluation indicator of any evaluation object in the normalized performance evaluation matrix, calculate the standard deviation and conflict quantization value of each performance evaluation indicator, obtain the information amount of each performance evaluation indicator, calculate the information amount of each performance evaluation indicator, and obtain the weight assignment of each performance evaluation indicator of any evaluation object.

4. The method for evaluating the effectiveness of a police reconnaissance cloud platform system according to claim 1, characterized in that: In the step of obtaining the performance evaluation value of each evaluation object, the performance evaluation value of any evaluation object is obtained according to the distance from the performance of any evaluation object to the positive and negative ideal solutions, specifically: The distance from the performance of any evaluation object to the negative ideal solution is divided by the sum of the distances from the performance of any evaluation object to the positive and negative ideal solutions to obtain the performance evaluation value of any evaluation object.

5. A performance evaluation system for a police reconnaissance cloud platform system, characterized in that: The following units are included: Establishing the effectiveness evaluation system unit: Based on the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established using the hierarchical analysis method; Constructing the effectiveness evaluation matrix unit: according to the effectiveness evaluation index system of the police reconnaissance cloud platform system, collecting the values ​​of each effectiveness evaluation index of each evaluation object to obtain the effectiveness evaluation matrix, normalizing the values ​​of each effectiveness evaluation index of each evaluation object in the effectiveness evaluation matrix to obtain the normalized effectiveness evaluation matrix; Obtaining the performance evaluation value unit of any evaluation object: using the objective weighting method to calculate the weight assignment of each performance evaluation index of any evaluation object in the normalized performance evaluation matrix, using the TOPSIS method to calculate and obtain the distance from the performance of any evaluation object to the positive and negative ideal solutions according to the weight assignment of each performance evaluation index of any evaluation object and the maximum and minimum values ​​of each performance evaluation index in all evaluation objects, and obtaining the performance evaluation value of any evaluation object according to the distance from the performance of any evaluation object to the positive and negative ideal solutions; Obtaining effectiveness evaluation result unit: sorting the effectiveness evaluation values ​​of all evaluation objects to obtain the effectiveness evaluation result of the police reconnaissance cloud platform system; In the step of establishing the effectiveness evaluation system, the effectiveness evaluation index system of the police reconnaissance cloud platform system is established by using the hierarchical analysis method, specifically: According to the functional characteristics of the police reconnaissance cloud platform system, the effectiveness evaluation indicators of the police reconnaissance cloud platform system are divided into several first-level indicators at the criterion level and second-level indicators at the execution level; Among them, the first-level indicators of the criterion layer include: information perception ability, feature analysis ability, and action decision-making ability; the information perception ability also includes the following second-level indicators of the execution layer: facial attribute perception ability, behavioral attribute perception ability, motor vehicle attribute perception ability, and non-motor vehicle attribute perception ability; the feature analysis ability also includes the following second-level indicators of the execution layer: recognition accuracy rate and effective alarm rate; the action decision-making ability also includes the following second-level indicators of the execution layer: intelligence processing timeliness, rationality of personnel allocation, and effective utilization rate of equipment; The execution layer secondary indicators also include: The secondary indicators of the execution layer can be divided into benefit indicators and cost indicators according to different attributes; among them, benefit indicators include: facial attribute perception ability, behavioral attribute perception ability, motor vehicle attribute perception ability, non-motor vehicle attribute perception ability, rationality of personnel allocation, and effective utilization rate of equipment; cost indicators include: recognition accuracy, effective alarm rate, and timeliness of intelligence processing; The method for obtaining the benefit-based indicator includes: Through artificial intelligence recognition algorithms, the attributes of faces, behaviors, motor vehicles and non-motor vehicles are captured, and the number of target attribute feature data that can be perceived and recognized is used as the basis for evaluating information perception capabilities to achieve information perception; Determine the rationality of personnel allocation and effective utilization of equipment through expert evaluation; The method for obtaining the cost-based indicator includes: Obtain the number of false recognitions and the number of invalid alarms, determine the false recognition rate according to the number of false recognitions, and determine the valid alarm rate according to the number of invalid alarms; The timeliness of intelligence processing is determined based on the time of intelligence acquisition and the time of action strategy formulation. The shorter the intelligence processing timeliness is, the higher the timeliness is.

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