Police force resource allocation method and device

Abstract

The present application relates to a method and device for allocating police resources, and belongs to the field of computer technology. The method comprises: obtaining influencing factor information of various influencing factors in a target area, where influencing factors refer to factors that affect the allocation of police resources in the target area; determining the degree of influence of influencing factors on police resources; allocating police resources to the target area based on the influencing factor information and the degree of influence; the problem that the current allocation of police resources lacks reasonable analysis of police force ratio, and when police resources are limited, there is a lack of reliable auxiliary tools to support the judgment of whether the current police force ratio of each area is reasonable, resulting in the inability to reasonably and effectively allocate police resources; since the degree of influence of police resource influencing factors on police resources can be determined, police resources can be allocated to the target area based on the degree of influence, which can improve the rationality of the police force allocation process and effectively allocate police resources.

Description

[Technical field]

[0001] The present application relates to a method and device for allocating police resources, and belongs to the field of computer technology. [Background technology]

[0002] The optimal allocation of police resources refers to adjusting the distribution of police forces in different regions and departments of public security organs, improving the age and skill structures of police officers to make them more reasonable, optimizing the management model of the police force, and improving the work efficiency of the police force.

[0003] Since the factors that affect the allocation of police resources are different in different areas, such as the number of alarms, population, geographical area, subway entrance passenger flow and number of key locations, the demand for police resources in different areas is also different.

[0004] At present, the allocation of police resources mainly adopts the manual allocation method, that is, the allocation personnel allocate police resources according to the size of the influencing factors in different regions and their own work experience.

[0005] However, the current allocation of police resources lacks reasonable analysis of police force ratios. In the case of limited police resources, there is a lack of reliable auxiliary tools to support the judgment of whether the current police force ratios in each region are reasonable, resulting in the inability to reasonably and effectively allocate police resources. [Summary of the invention]

[0006] This application provides a method and device for allocating police resources, which can solve the problem that the current police resource allocation lacks reasonable analysis of the police force ratio. In the case of limited police resources, there is a lack of reliable auxiliary tools to support the judgment of whether the current police force ratio in each area is reasonable, resulting in the inability to reasonably and effectively allocate police resources. This application provides the following technical solutions:

[0007] In a first aspect, a method for allocating police resources is provided, the method comprising:

[0008] Acquire influencing factor information of various influencing factors in the target area, wherein the influencing factors refer to factors that affect the allocation of police resources in the target area;

[0009] Determine the degree to which the influencing factors affect the police resources;

[0010] Police resources are allocated to the target area based on the influencing factor information and the degree of influence.

[0011] Optionally, determining the degree of influence of the influencing factors on the police resources includes:

[0012] Obtain at least two sets of sample data, each set of sample data including historical police force resource information and historical influencing factor information corresponding to the historical police force resources;

[0013] Clustering the at least two groups of sample data using a clustering algorithm to obtain at least one group of cluster sets; the historical police resource information of different sample data in each group of cluster sets is the same, and the historical influencing factor information of the designated influencing factors in different sample data in each group of cluster sets is the same;

[0014] Calculate the social stability value corresponding to each cluster set;

[0015] Extracting the target cluster set whose social stability value meets the preset conditions;

[0016] The influence degree of historical influencing factors on historical police resources is determined based on the sample data in the target cluster set, and the influence degree of the influencing factors on the police resources is obtained.

[0017] Optionally, clustering the at least two groups of sample data using a clustering algorithm to obtain at least one group of cluster sets includes:

[0018] Extracting a designated influencing factor from the different historical influencing factors based on the business relevance between the different historical influencing factors;

[0019] The clustering algorithm is used to cluster the at least two groups of sample data based on the historical influencing factor information of the designated influencing factor and the corresponding historical police resource information to obtain at least one cluster set.

[0020] Optionally, clustering the at least two groups of sample data using a clustering algorithm to obtain at least one group of cluster sets includes:

[0021] Each group of sample data is clustered using a density-based clustering algorithm to obtain clustering information.

[0022] Optionally, calculating the social stability value corresponding to each cluster set includes:

[0023] Select at least one evaluation factor from each historical influencing factor;

[0024] The weighted average value of the historical influencing factor information corresponding to the at least one evaluation factor is calculated to obtain the social stability value.

[0025] Optionally, determining the influence degree of historical influencing factors on historical police resources based on the sample data in the target cluster set to obtain the influence degree of the influencing factors on the police resources includes:

[0026] Based on the sample data in the target cluster set, a correlation coefficient matrix between each historical influencing factor and the historical police resources is established;

[0027] The correlation coefficients between historical influencing factors and historical police resources are extracted from the correlation coefficient matrix to obtain the degree of influence.

[0028] Optionally, the influence degree is represented by the weight of the influence factor, and the allocating police resources to the target area based on the influence factor information and the influence degree includes:

[0029] The sum of the products of each influencing factor information and the corresponding weight is calculated to obtain the police force resource information of the target area.

[0030] Optionally, the acquiring influencing factor information of each influencing factor of the target area includes:

[0031] Influencing factor information of each influencing factor of the target area is collected in a specified time period.

[0032] Optionally, the specified time period is a time period in which the population flow rate is less than a preset threshold.

[0033] In a second aspect, a police force resource allocation device is provided, the device comprising

[0034] A factor acquisition module, used to acquire influencing factor information of various influencing factors in the target area, wherein the influencing factors refer to factors that affect the allocation of police resources in the target area;

[0035] An impact determination module, used to determine the impact degree of the influencing factors on the police resources;

[0036] An allocation calculation module is used to allocate police resources to the target area based on the influencing factor information and the degree of influence.

[0037] The beneficial effects of the present application include at least: obtaining the influencing factor information of various influencing factors in the target area, where the influencing factors refer to the factors that affect the allocation of police resources in the target area; determining the degree of influence of the influencing factors on the police resources; allocating police resources to the target area based on the influencing factor information and the degree of influence; it can solve the problem that the current allocation of police resources lacks reasonable analysis of the police force ratio, and when the police resources are limited, there is a lack of reliable auxiliary tools to support the judgment of whether the current police force ratio of each area is reasonable, resulting in the inability to reasonably and effectively allocate police resources; since the degree of influence of the police resource influencing factors on the police resources can be determined, the police resources are allocated to the target area based on the degree of influence, which can improve the rationality of the police force allocation process and effectively allocate police resources.

[0038] In addition, since a clustering algorithm is used to cluster at least two groups of sample data to obtain at least one group of cluster sets, it is convenient to divide the sample data samples into multiple classes. The degree of influence of the police resource influencing factors on the police resources in each class is consistent, which facilitates comprehensive analysis of similar sample data in the sample data, so the accuracy of the calculated degree of influence of the police resource influencing factors on the police resources can be improved.

[0039] In addition, based on the business relevance between different historical influencing factors, the designated influencing factors are extracted from the different historical influencing factors; using a clustering algorithm, at least two groups of sample data are clustered based on the historical influencing factor information of the designated influencing factors and the corresponding historical police resource information to obtain at least one cluster set; this can solve the problem that there are many types of influencing factors, but there may be only a part of the influencing factors that mainly affect data clustering, and the more influencing factors are used in clustering, the more categories will be obtained, which is not conducive to data clustering. Since some designated influencing factors can be extracted from multiple influencing factors to cluster the sample data, the effectiveness of clustering can be guaranteed.

[0040] In addition, since the Dbscan algorithm can identify noise data in the sample data during the process of clustering at least two groups of sample data, and can exclude sample data collected when the population flow is large, the accuracy of the calculated degree of influence of factors affecting police resources on police resources can be further improved.

[0041] In addition, since the social stability value corresponding to each group of cluster sets is calculated; the target cluster sets whose social stability values ​​meet the preset conditions are extracted, a cluster set with a more reasonable allocation of police resources can be selected from the cluster sets, which can further improve the accuracy of the calculated degree of influence of police resource influencing factors on police resources.

[0042] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present application in conjunction with the accompanying drawings.

Brief Description of the Drawings

[0043] Figure 1 is a schematic diagram of a police resource allocation method provided by an embodiment of the present application;

[0044] Figure 2 This is a schematic diagram of the principle of the Dbscan clustering algorithm provided by an embodiment of the present application;

[0045] Figure 3is a schematic diagram of a correlation coefficient matrix provided by an embodiment of the present application;

[0046] Figure 4 is a flow chart of a method for allocating police resources provided by an embodiment of the present application;

[0047] Figure 5 is a block diagram of a police resource allocation device provided by an embodiment of the present application; [Specific implementation method]

[0048] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0049] Optionally, the present application uses the police resource allocation method provided in each embodiment as an example for use in an electronic device, where the electronic device is a terminal or a server. The terminal may be a mobile phone, a computer, a tablet computer, etc. This embodiment does not limit the type of electronic device.

[0050] Figure 1 This is a flow chart of a method for allocating police resources provided by an embodiment of the present application, which method includes at least the following steps:

[0051] Step 101, obtaining influencing factor information of various influencing factors in the target area, where the influencing factors refer to factors that affect the allocation of police resources in the target area.

[0052] Among them, the influencing factors include natural factors and social factors in the target area.

[0053] Optionally, the influencing factors include: the number of registered households, the number of migrant population, the area of ​​the region, the number of traffic light intersections, the number of roads, the number of police stations, the number of cases filed and / or the number of cases solved. The influencing factor information is a numerical value corresponding to the influencing factor, which can be a real collected numerical value or a numerical value obtained after normalization. This embodiment does not limit the implementation method of the influencing factor information.

[0054] Optionally, the police resources include: the number of police officers, the number of police cars, etc., which are factors related to the police force configuration. The police resource information is the value corresponding to the police resource, which can be a real collected value or a processed value. This embodiment does not limit the implementation method that affects the police resource information.

[0055] Optionally, acquiring the influencing factor information of each influencing factor of the target area includes: collecting the influencing factor information of each influencing factor of the target area in a specified time period.

[0056] Since population-related factors such as the number of foreign population will affect the allocation of police resources, the data collected during the time period with high population mobility cannot accurately reflect the actual situation of the target area. Therefore, the designated time period is the time period when the population mobility is less than the preset threshold. This can avoid the impact of large-scale population mobility on the allocation of police resources and ensure that the collected data can accurately reflect the actual situation of the target area.

[0057] Optionally, the population flow rate of the target area is the number of people entering or leaving the target area within a preset time period.

[0058] The preset duration may be 5 hours, or may be 1 day. This embodiment does not limit the preset duration.

[0059] Optionally, the preset threshold is determined according to the average annual population flow rate of the target area, or according to the average population flow rate on statutory holidays in the target area. This embodiment does not limit the method for determining the preset threshold.

[0060] Step 102, determining the degree of influence of the influencing factors on police resources.

[0061] Optionally, determining the degree of influence of influencing factors on police resources includes: obtaining at least two groups of sample data, each group of sample data including historical police resource information and historical influencing factor information corresponding to the historical police resources; clustering the at least two groups of sample data using a clustering algorithm to obtain at least one group of cluster sets; the historical police resource information of different sample data in each cluster set is the same, and the historical influencing factor information of specified influencing factors in different sample data in each cluster set is the same; calculating the social stability value corresponding to each cluster set; extracting a target cluster set whose social stability value meets preset conditions; determining the degree of influence of historical influencing factors on historical police resources based on the sample data in the target cluster set, and obtaining the degree of influence of the influencing factors on police resources.

[0062] Optionally, the historical influencing factors are of the same type as the influencing factors; the historical police resources are of the same type as the police resources.

[0063] Indicatively, the social stability value is negatively correlated with the social stability level. At this time, the preset conditions include but are not limited to the following:

[0064] The first method is to arrange the social stability of all cluster sets in order from small to large, and determine the top n cluster sets as the target cluster sets. n is a positive integer.

[0065] The second method is to determine the cluster set whose social stability value is less than a preset threshold among all cluster sets as the target cluster set.

[0066] In other embodiments, the social stability value may also be positively correlated with the social stability level. Accordingly, the preset condition may also be to select a target cluster set with a greater social stability level from each cluster set. This embodiment does not limit the method of selecting the target cluster set.

[0067] Optionally, the sample data is also collected in a specified time period, and the specified time periods and / or collection locations of different groups of sample data are different.

[0068] Optionally, since the same influencing factor has different degrees of influence on police resources in different types of areas, in order to improve the accuracy of the calculated degree of influence of the influencing factor on police resources, the degree of influence of the influencing factor on police resources is calculated separately for different types of areas.

[0069] In one example, the different types of areas include suburban and urban areas.

[0070] Optionally, since there are many types of influencing factors, but there may be only a part of the influencing factors that mainly affect data clustering, and the more influencing factors are used in clustering, the more categories will be obtained, which is not conducive to data clustering. Based on this, a clustering algorithm is used to cluster at least two groups of sample data to obtain at least one group of cluster sets, including: based on the business relevance between different historical influencing factors, a specified influencing factor is extracted from different historical influencing factors; a clustering algorithm is used to cluster at least two groups of sample data based on the historical influencing factor information of the specified influencing factor and the corresponding historical police resource information to obtain at least one group of cluster sets. In this way, some specified influencing factors can be extracted from a variety of influencing factors to cluster the sample data, which can ensure the effectiveness of clustering.

[0071] Among them, based on the business relevance between different historical influencing factors, the designated influencing factors are extracted from the different historical influencing factors, including: analyzing the correlation coefficients between different historical influencing factors, extracting the historical influencing factors whose correlation coefficients are greater than a preset threshold, and determining the combination of historical influencing factors whose correlation coefficients are greater than the preset threshold as the designated influencing factors.

[0072] Accordingly, at least two groups of sample data are clustered based on the historical influencing factor information of the specified influencing factors and the corresponding historical police resource information, including: clustering at least two sample data based on a combination of influencing factor values ​​of historical influencing factors whose correlation coefficients are greater than a preset threshold and the corresponding police resource information.

[0073] Among them, the correlation between different historical influencing factors is positively correlated with the correlation coefficient, that is, the stronger the correlation between different historical influencing factors, the larger the correlation coefficient.

[0074] For example, if the correlation coefficient between the total foreign population in the region and the regional area in the historical influencing factors is greater than the preset threshold, the combination of the regional population and the regional area is determined as the designated influencing factor, and accordingly, the ratio of the regional population to the regional area is the influencing factor information of the designated influencing factor.

[0075] For example, the specified influencing factors and the corresponding influencing factor information extracted from different historical influencing factors are:

[0076] Factor 1: total population of the region / regional area;

[0077] Factor 2: Number of signalized intersections / area;

[0078] Factor 3: Regional registered population / immigrant population (people coming to a city + people from abroad);

[0079] Factor 4: Number of business districts and large venues / area;

[0080] Factor 5: Number of business districts and large venues / total population of the region;

[0081] Factor 6: Number of branch offices / number of 110 issued in the region;

[0082] Factor 7: Number of staff members in the branch / number of front-line law enforcement police officers in the branch.

[0083] Optionally, the business relevance between different historical influencing factors is analyzed by using a drill-down analysis method.

[0084] In this embodiment, based on the sample data obtained, the above seven categories of designated influencing factors are selected as basic features for cluster analysis. The analysis angle needs to be clustered from the different social status levels that need to be protected in each target area. At the same time, through the drill-down analysis method, according to the business relevance between the social factors, the class-designated influencing factors based on the original factor data are proposed, and the above seven categories of designated influencing factors are clustered. Each type of designated influencing factor mainly represents the characteristics of the region to the greatest extent according to the data situation. By selecting the above factors, a better clustering effect can be achieved.

[0085] In one example, the sample data includes sample data collected from different types of areas. Since the same influencing factor has different degrees of influence on police resources in different types of areas, the sample data collected from different types of areas are located in different cluster sets.

[0086] In order to obtain accurate clustering results, this embodiment does not limit the number of cluster sets obtained after clustering. Therefore, a clustering algorithm is used to cluster at least two groups of sample data to obtain at least one group of cluster sets, including: using a density-based clustering algorithm to cluster each group of sample data to obtain clustering information.

[0087] Optionally, the density-based clustering algorithm may be a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, or an OPTICS (Ordering Points To Identify the Clustering Structure) algorithm, or a DENCLUE (DENsitybased CLUstEring) algorithm. This embodiment does not limit the type of the density-based clustering algorithm.

[0088] See also Figure 2 In one example, the DBSCAN algorithm is used to cluster the data of each group. The DBSCAN algorithm is a density-based clustering algorithm. The number of clusters does not need to be specified in advance during the clustering process. However, in the clustering results, the data points are mainly classified into the following three categories:

[0089] The first category: core points, that is, points with a number exceeding MinPts within the radius Eps;

[0090] The second category: boundary points, that is, points whose number within the radius Eps is less than MinPts but fall within the area of ​​the core points;

[0091] The third category: noise points, that is, points that are neither core points nor boundary points.

[0092] Among them, Eps and MinPts are preset constants.

[0093] Optionally, reduce the number of noise points by adjusting the radius Eps multiple times.

[0094] In one example, the number of sample data is 240 groups, and the number of noise point sample data needs to be controlled to be less than 10% of the data, that is, the number of noise point data should not exceed 24 groups. Based on this idea, the Eps radius is adjusted to 0.235, and the number of noise data in 240 groups of data is 20 groups, which effectively reaches the remaining number that can be clustered.

[0095] Since the Dbscan algorithm can identify noise data in the sample data during the process of clustering at least two groups of sample data, and can exclude sample data collected when the population flow is large, the accuracy of the calculated degree of influence of factors affecting police resources on police resources can be further improved.

[0096] Since the sample data are different based on the dimension, optionally, before clustering the at least two groups of sample data using a clustering algorithm to obtain at least one group of cluster sets, the method further includes: normalizing the sample data.

[0097] Optionally, the normalization process may adopt a min-max normalization method, or may adopt a Z-score normalization method. This embodiment does not limit the normalization process method.

[0098] In one example, the min-max normalization method normalizes the sample data.

[0099] Optionally, calculating the social stability value corresponding to each cluster set includes: selecting at least one evaluation factor from various historical influencing factors; calculating the weighted average of the historical influencing factor information corresponding to the at least one evaluation factor to obtain the social stability value.

[0100] Optionally, the evaluation factors include, but are not limited to: the number of police reports per capita, the number of cases filed per capita, and / or the number of cases received per capita.

[0101] Since the historical influencing factors of per capita number of police reports, per capita number of cases filed, and per capita number of cases received can all represent the stability of the region, the evaluation factors are determined as per capita number of police reports, per capita number of cases filed, and per capita number of cases received, and the weights of per capita number of police reports, per capita number of cases filed, and per capita number of cases received are the same, then the social stability value is per capita number of police reports, per capita number of cases filed, and per capita number of cases received divided by 3. At this time, the social stability value is negatively correlated with the social stability level, that is, the smaller the social stability value, the more stable the social security level of the area is.

[0102] Since the evaluation factors differ based on the dimensions, optionally, before calculating the weighted average of the historical influencing factor information corresponding to at least one evaluation factor, the method further includes: normalizing the historical influencing factor information corresponding to the at least one evaluation factor.

[0103] Optionally, calculating the social stability value corresponding to each group of cluster sets includes: for each cluster set, calculating the social stability value of each sample data in the cluster set, and taking the average of the social stability values ​​of all sample data in the cluster set as the social stability value of the cluster set.

[0104] Optionally, the degree of influence of historical influencing factors on historical police resources is determined based on sample data in the target cluster set, including: establishing a correlation coefficient matrix between each historical influencing factor and historical police resources based on sample data in the target cluster set; extracting the correlation coefficient between the historical influencing factors and historical police resources from the correlation coefficient matrix to obtain the degree of influence.

[0105] See also Figure 3 The horizontal and vertical axes of the correlation matrix are historical police resources and historical influencing factors. The values ​​in the matrix are used to reflect the impact of various historical influencing factors on historical police resources. Each value in the matrix represents the correlation between factors, ranging from -1 to 1. 0 means that the two factors are linearly uncorrelated. The closer the absolute value is to 1, the stronger the correlation between the two factors. The farther the absolute value is from 1, the smaller the correlation between the two factors.

[0106] Optionally, based on the sample data in the target cluster set, a correlation coefficient matrix between each historical influencing factor and historical police resources is established, including: based on the historical police resource information corresponding to each group of sample data in the cluster set and the historical influencing factor information corresponding to the historical police resources, a relationship matrix between historical influencing factors and historical police resources is established.

[0107] Optionally, the correlation coefficient between historical influencing factors and historical police resources is extracted from the correlation coefficient matrix to obtain the degree of influence, including: based on the correlation coefficient between historical influencing factors and historical police resources, calculating the weight of the historical influencing resources affecting historical police resources, where the weight is the degree of influence.

[0108] Optionally, a nonlinear programming approach is used to calculate the weight of the historical influence resources on the historical police resources.

[0109] Step 103, allocating police resources to the target area based on the influencing factor information and the degree of influence.

[0110] Optionally, the degree of influence is represented by the weight of the influencing factors, and police resources are allocated to the target area based on the influencing factor information and the degree of influence, including: calculating the sum of the products of each influencing factor information and the corresponding weight to obtain the police resource information of the target area.

[0111] In summary, the police resource allocation method provided in this embodiment obtains the influencing factor information of each influencing factor in the target area, where the influencing factor refers to the factor that affects the allocation of police resources in the target area; determines the degree of influence of the influencing factor on the police resources; and allocates police resources to the target area based on the influencing factor information and the degree of influence. This can solve the problem that the current allocation of police resources lacks reasonable analysis of police force ratios, and when police resources are limited, there is a lack of reliable auxiliary tools to support the judgment of whether the current police force ratios of each area are reasonable, resulting in the inability to reasonably and effectively allocate police resources. Since the degree of influence of police resource influencing factors on police resources can be determined, police resources can be allocated to the target area based on the degree of influence, which can improve the rationality of the police force allocation process and effectively allocate police resources.

[0112] In addition, since a clustering algorithm is used to cluster at least two groups of sample data to obtain at least one group of cluster sets, it is convenient to divide the sample data samples into multiple classes. The degree of influence of the police resource influencing factors on the police resources in each class is consistent, which facilitates comprehensive analysis of similar sample data in the sample data, so the accuracy of the calculated degree of influence of the police resource influencing factors on the police resources can be improved.

[0113] In addition, based on the business relevance between different historical influencing factors, the designated influencing factors are extracted from the different historical influencing factors; using a clustering algorithm, at least two groups of sample data are clustered based on the historical influencing factor information of the designated influencing factors and the corresponding historical police resource information to obtain at least one cluster set; this can solve the problem that there are many types of influencing factors, but there may be only a part of the influencing factors that mainly affect data clustering, and the more influencing factors are used in clustering, the more categories will be obtained, which is not conducive to data clustering. Since some designated influencing factors can be extracted from multiple influencing factors to cluster the sample data, the effectiveness of clustering can be guaranteed.

[0114] In addition, since the Dbscan algorithm can identify noise data in the sample data during the process of clustering at least two groups of sample data, and can exclude sample data collected when the population flow is large, the accuracy of the calculated degree of influence of factors affecting police resources on police resources can be further improved.

[0115] In addition, since the social stability value corresponding to each group of cluster sets is calculated; the target cluster sets whose social stability values ​​meet the preset conditions are extracted, a cluster set with a more reasonable allocation of police resources can be selected from the cluster sets, which can further improve the accuracy of the calculated degree of influence of police resource influencing factors on police resources.

[0116] In order to more clearly understand the police resource allocation method provided by this application, an example is given below to illustrate the method. Figure 4 As shown, the method includes at least the following steps:

[0117] Step 401, obtaining influencing factor information of each influencing factor of the target area;

[0118] Step 402, obtaining at least two groups of sample data, each group of sample data including historical police force resource information and historical influencing factor information corresponding to the historical police force resources;

[0119] Step 403, extracting a designated influencing factor from different historical influencing factors based on the business relevance between different historical influencing factors;

[0120] Step 404, using a clustering algorithm, clustering at least two groups of sample data based on historical influencing factor information of a designated influencing factor and corresponding historical police resource information to obtain at least one cluster set;

[0121] Step 405, selecting at least one evaluation factor from each historical influencing factor;

[0122] Step 406, calculating the weighted average of the historical influencing factor information corresponding to at least one evaluation factor to obtain a social stability value;

[0123] Step 407, extracting a target cluster set whose social stability value meets a preset condition;

[0124] Step 408, based on the sample data in the target cluster set, establish a correlation coefficient matrix between each historical influencing factor and historical police resources;

[0125] Step 409, extracting the correlation coefficient between the historical influencing factors and the historical police resources from the correlation coefficient matrix;

[0126] Step 410, based on the correlation coefficient between the historical influencing factors and the historical police resources, calculate the weight of the historical influencing resources affecting the historical police resources;

[0127] Step 411, calculate the sum of the products of each influencing factor information and the corresponding weight to obtain the police resource information of the target area.

[0128] The relevant description of this embodiment refers to the above embodiment, and this embodiment will not be described in detail here.

[0129] According to the above embodiments, the police resource allocation method for self-mobile equipment provided by the present application extracts specified influencing factors from different historical influencing factors based on the business relevance between different historical influencing factors; uses a clustering algorithm to cluster at least two groups of sample data based on the historical influencing factor information of the specified influencing factors and the corresponding historical police resource information to obtain at least one group of cluster sets; it can solve the problem that there are many types of influencing factors, but there may be only a part of the influencing factors that mainly affect data clustering, and the more influencing factors are used in clustering, the more categories will be obtained in the end, which is not conducive to data clustering; since some specified influencing factors can be extracted from multiple influencing factors to cluster sample data, the effectiveness of clustering can be guaranteed, and some specified influencing factors can be extracted from multiple influencing factors to cluster sample data, the effectiveness of clustering can be guaranteed.

[0130] Figure 55 is a block diagram of a police resource allocation device provided by an embodiment of the present application. The device comprises at least the following modules: a factor acquisition module 510 , an influence determination module 520 and an allocation calculation module 530 .

[0131] A factor acquisition module 510 is used to acquire influencing factor information of various influencing factors in the target area, where the influencing factors refer to factors that affect the allocation of police resources in the target area;

[0132] An impact determination module 520, for determining the degree of impact of the impact factor on police resources;

[0133] The allocation calculation module 530 is used to allocate police resources to the target area based on the influencing factor information and the degree of influence.

[0134] For relevant details, refer to the above method embodiment.

[0135] It should be noted that: the police force resource allocation device provided in the above embodiment only uses the division of the above functional modules as an example to illustrate when allocating police force resources. In actual applications, the above functional allocation can be completed by different functional modules as needed, that is, the internal structure of the police force resource allocation device is divided into different functional modules to complete all or part of the functions described above. In addition, the police force resource allocation device provided in the above embodiment and the police force resource allocation method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0136] Optionally, the present application also provides a computer-readable storage medium, in which a program is stored, and the program is loaded and executed by a processor to implement the police resource allocation method of the above method embodiment.

[0137] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0138] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for allocating police resources, characterized in that: The method comprises: Acquire influencing factor information of various influencing factors in the target area, wherein the influencing factors refer to factors that affect the allocation of police resources in the target area; Determine the degree to which the influencing factors affect the police resources; Allocate police resources to the target area based on the influencing factor information and the degree of influence; Determining the degree of influence of the influencing factors on the police resources includes: Obtain at least two sets of sample data, each set of sample data including historical police force resource information and historical influencing factor information corresponding to the historical police force resources; Clustering the at least two groups of sample data using a clustering algorithm to obtain at least one group of cluster sets; the historical police resource information of different sample data in each group of cluster sets is the same, and the historical influencing factor information of the designated influencing factors in different sample data in each group of cluster sets is the same; Calculate the social stability value corresponding to each cluster set; Extracting the target cluster set whose social stability value meets the preset conditions; The influence degree of historical influencing factors on historical police resources is determined based on the sample data in the target cluster set, and the influence degree of the influencing factors on the police resources is obtained.

2. The method according to claim 1, characterized in that The clustering algorithm is used to cluster the at least two groups of sample data to obtain at least one group of cluster sets, including: Extracting a designated influencing factor from the different historical influencing factors based on the business relevance between the different historical influencing factors; The clustering algorithm is used to cluster the at least two groups of sample data based on the historical influencing factor information of the designated influencing factor and the corresponding historical police resource information to obtain at least one cluster set.

3. The method according to claim 1, characterized in that The clustering algorithm is used to cluster the at least two groups of sample data to obtain at least one group of cluster sets, including: Each group of sample data is clustered using a density-based clustering algorithm to obtain clustering information.

4. The method according to claim 1, characterized in that: The calculating of the social stability value corresponding to each cluster set includes: Select at least one evaluation factor from each historical influencing factor; The weighted average value of the historical influencing factor information corresponding to the at least one evaluation factor is calculated to obtain the social stability value.

5. The method according to claim 1, characterized in that The determining the influence degree of historical influencing factors on historical police resources based on the sample data in the target cluster set to obtain the influence degree of the influencing factors on the police resources includes: Based on the sample data in the target cluster set, a correlation coefficient matrix between each historical influencing factor and the historical police resources is established; The correlation coefficients between historical influencing factors and historical police resources are extracted from the correlation coefficient matrix to obtain the degree of influence.

6. The method according to claim 1, characterized in that The degree of influence is represented by the weight of the influencing factor, and the allocating police resources to the target area based on the influencing factor information and the degree of influence includes: The sum of the products of each influencing factor information and the corresponding weight is calculated to obtain the police force resource information of the target area.

7. The method according to claim 1, characterized in that The obtaining of influencing factor information of each influencing factor of the target area includes: Influencing factor information of each influencing factor of the target area is collected in a specified time period.

8. The method according to claim 7, characterized in that The specified time period is a time period when the population flow rate is less than a preset threshold.

9. A police resource allocation device using the method according to any one of claims 1 to 8, characterized in that: The device comprises: A factor acquisition module, used to acquire influencing factor information of various influencing factors in the target area, wherein the influencing factors refer to factors that affect the allocation of police resources in the target area; An impact determination module, used to determine the impact degree of the influencing factors on the police resources; An allocation calculation module is used to allocate police resources to the target area based on the influencing factor information and the degree of influence.

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