New business state public security open management comprehensive service system, device and method

Abstract

The invention provides a new business state public security open management comprehensive service system, device and method, and relates to the technical field of computer information analysis and public security management. Historical public security feature data related to a new business state is used, and feature indexes such as a public security event occurrence index and a social media crisis index are calculated based on the data; the method comprises the following steps: determining a public security management risk level, scoring data in the past three years to determine a public security management risk level, outputting a risk level index by using a deep learning network, obtaining feedback data such as public security event report and satisfaction score based on a user, generating a feedback regulation factor to adjust a public security management risk correction coefficient in the current three months, and finally setting a threshold interval. And comparing the correction coefficients to determine whether to upgrade or degrade the risk level, and formulating corresponding safety response measures according to different levels. According to the invention, through combination of data acquisition and a deep learning model, accurate prediction and dynamic management of new business state public security risks are realized.

Description

Technical Field

[0001] The present invention relates to the technical fields of computer information analysis and public security management, and particularly to a comprehensive service system, device and method for open management of public order in new business forms. Background Art

[0002] In recent years, with the acceleration of urbanization and the development of social economy, new business forms have emerged rapidly, such as the sharing economy, e-commerce, etc. While bringing convenience to society, these new business forms have also triggered a series of public security management challenges. Traditional public security management models often struggle to adapt to the characteristics of these new business forms, leading to the complication of public security issues, such as diverse forms of crime and low efficiency in handling incidents. Therefore, there is an urgent need for a comprehensive public security management system to achieve effective supervision and service for new business forms.

[0003] Currently, public security management technology is developing towards the direction of intelligence and digitization. Many cities have started to introduce advanced technologies such as big data and artificial intelligence to improve the efficiency and accuracy of public security management. For example, through data analysis, real-time monitoring and early warning of suspicious behaviors can be achieved. At the same time, building an open public security management platform helps to enhance public participation and information sharing. Despite certain progress, further integration of various resources and technologies is still required to form a comprehensive and efficient public security management comprehensive service system.

[0004] In the existing technology, there is a common phenomenon of data islands in the public security management of new business forms, lacking comprehensive analysis and comprehensive evaluation of emerging business activities. This has led to insufficient ability to identify and respond to public security incidents. Traditional management models often cannot quickly adapt to the challenges brought by new business forms, and it is difficult to obtain and analyze public security feature data related to new business forms in real time, thus affecting the effective handling of public security incidents and the sense of security of users.

[0005] In addition, existing systems usually lack intelligent risk prediction capabilities and are difficult to effectively combine user feedback with historical data. Therefore, they cannot accurately evaluate the risk level of public security management. This limitation makes public security management show problems of slow response and low efficiency in dealing with a dynamically changing environment, and it is unable to timely adjust management strategies to cope with potential security risks, thus affecting the effectiveness and credibility of overall public security management.

[0006] Therefore, it is necessary to provide a comprehensive service system, device and method for open management of public order in new business forms to solve the above problems.

[0007] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure. Therefore, it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0008] The purpose of the present invention is to provide a comprehensive service system, device and method for the open management of public security in a new business format to solve the problems raised in the above-mentioned background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] A comprehensive service system for the open management of public security in a new business format, the specific steps include:

[0011] A data collection and prediction module, which is used to obtain historical public security feature data related to the new business format in multiple past historical time periods through the public security computer system. The historical public security feature data includes the total number of business transaction activities related to the new business format, the total number of public security incidents, the number of similar public security incidents, the total number of negative comments, the total number of comments, the average response time of public security incidents, and the area of the area under public security management, and predict the public security feature data related to the new business format within the current three months based on the public security computer system;

[0012] A feature index calculation module, which calculates and generates a feature index for characterizing the public security status of the new business format based on the obtained historical public security feature data. The feature index includes a public security incident occurrence index, a social media crisis index, a public security response efficiency index, a recurrence rate index, and a public security incident location density index, and scores the feature index related to the new business format in the past three years based on the historical public security data of the new business format in the public security system to determine its public security management risk level index. The public security management risk level index includes low risk, medium risk, and high risk;

[0013] A public security risk prediction model module, which constructs a new business format public security risk prediction model with the feature index as the input and the public security management risk level index as the output based on a deep learning network, divides the historical public security feature data in the past three years, and evenly divides it into public security feature data for each three months, and performs model training based on the feature index and public security management risk level index related to the new business format every three months, and inputs the public security feature index related to the new business format within the current three months into the model to obtain the public security management risk level index;

[0014] A user feedback mechanism module, which is used to establish a feedback mechanism in the public security computer system to obtain feedback data from current new business format users on the open management of public security in the new business format. The feedback data includes the total number of public security incident reports, user satisfaction scores, and the resolution rate of public security incidents, generates a feedback adjustment factor based on the feedback data of new business format users, and combines the obtained feedback adjustment factor with the public security feature index related to the new business format within the current three months to comprehensively generate a public security management risk correction coefficient;

[0015] A risk level decision-making module, which is used to set the upper and lower limits of the threshold management range, compare the comprehensively generated public security management risk correction coefficient with the threshold management range, determine whether to upgrade or downgrade the public security management risk level index output by the model, so as to determine the final public security management risk level index, and set corresponding security response measures according to different public security management risk level indexes.

[0016] Furthermore, a characteristic index used to characterize the public security situation of the new business format is calculated based on the obtained historical public security characteristic data, and the method is as follows:

[0017] Based on the total number of business transactions and the total number of public security incidents in the public security-related characteristic data of the new business format, calculate the public security incident occurrence index, and the formula is:

[0018]

[0019] Among them, represents the public security incident occurrence index, 、 are the total number of public security incidents and the total number of business transactions respectively;

[0020] According to the total number of negative comments and the total number of comments in the public security-related characteristic data of the new business format, calculate the social media crisis index, and the formula is:

[0021]

[0022] Among them, represents the social media crisis index, 、 represent the total number of negative comments and the total number of comments respectively;

[0023] According to the average response time of public security incidents and the total number of public security incidents in the public security-related characteristic data of the new business format, calculate the public security response efficiency index, and the formula is:

[0024]

[0025] Among them, represents the public security response efficiency index, is the average response time of public security incidents;

[0026] According to the number of similar public security incidents and the total number of public security incidents in the public security-related characteristic data of the new business format, calculate the recurrence rate index, and the formula is:

[0027]

[0028] Among them, Denote the recurrence rate index, is the number of similar public security incidents;

[0029] Calculate the location density index of public security incidents based on the total number of public security incidents and the area of the region under public security management in the data related to the characteristics of public security in the new business form. The formula is as follows:

[0030]

[0031] Among them, Denote the location density index of public security incidents, is the area of the region under public security management.

[0032] Furthermore, build a new business form public security risk prediction model based on the deep learning network, with the input being the characteristic index and the output being the public security management risk level index. The method is as follows:

[0033] The new business form public security risk prediction model adopts a neural network convolutional structure, including an input layer, a hidden layer, and an output layer. The input layer is responsible for receiving the characteristic index that characterizes the public security situation of the new business form after extraction; the hidden layer is used to process the extracted characteristic index. By applying multiple convolutional kernels and using the ReLU activation function, a non-linear relationship is introduced to enable the model to fit complex characteristic relationships; an independent neuron is set in the output layer, which is responsible for converting the characteristic index representation extracted by the hidden layer into the final prediction result, that is, outputting the public security management risk level index.

[0034] Furthermore, generate public security management risk factors based on the feedback data of new business form users, and use the obtained public security management risk factors to comprehensively generate a public security management risk correction coefficient in combination with the public security characteristic index related to the new business form in the current three months. The method is as follows:

[0035] Obtain the feedback data of users on the open management of public security in the new business form, including the total number of reports of public security incidents, the user satisfaction score, and the resolution rate of public security incidents. Calculate the feedback adjustment factor based on the feedback data of the open management of public security in the new business form. The formula is as follows:

[0036]

[0037] Among them, Denote the feedback adjustment factor, is the total number of reports of public security incidents, is the user satisfaction score, and Adopt a full score system of ten points, is the resolution rate of public security incidents. The resolution rate of public security incidents is the ratio of the total number of resolved public security incidents to the total number of public security incidents;

[0038] The security management risk correction coefficient is comprehensively generated based on the security management risk factors calculated and combined with the characteristic index representing the security status of the new business format. The formula is as follows:

[0039]

[0040] Among them, represents the security management risk correction coefficient, 、 、 、 、 are the weight ratios of the respective corresponding characteristic indexes, and .

[0041] Furthermore, to determine the final security management risk level index, the method is as follows:

[0042] Set the upper and lower limits of the threshold management interval , the security management risk level indexes output by the model include low risk, medium risk and high risk. Compare the generated security management risk correction coefficient with the upper and lower limits of the threshold management interval. If , it indicates that no upgrading or downgrading process is required, and the level index output by the model is the final security management risk level index; if , it indicates that an upgrading process is required, and upgrade the level index output by the model by one level as the final security management risk level index; if , it indicates that a downgrading process is required, and downgrade the level index output by the model by one level as the final security management risk level index; set limiting conditions for the level index output by the model: when the security management risk level index output by the model is low risk, no downgrading process is required at this time; when the security management risk level index output by the model is high risk, no upgrading process is required at this time.

[0043] The present invention also provides a comprehensive service method for the open management of the security of the new business format. The comprehensive service method is used to execute the above-mentioned comprehensive service system for the open management of the security of the new business format, including:

[0044] Step 1: Obtain historical security characteristic data related to the new business format within multiple past historical time periods through the public security computer system. The historical security characteristic data includes the total number of business transaction activities related to the new business format, the total number of security incidents, the number of similar security incidents, the total number of negative comments, the total number of comments, the average response time of security incidents, and the area of the security management region, and predict the security characteristic data related to the new business format within the current three months based on the public security computer system;

[0045] Step 2: Calculate and generate a feature index for characterizing the public security situation of the new business form based on the obtained historical public security feature data. The feature index includes the public security incident occurrence index, the social media crisis index, the public security response efficiency index, the recurrence rate index, and the public security incident location density index. Score the feature index related to the new business form in the past three years based on the historical public security data of the new business form in the public security system to determine its public security management risk level index. The public security management risk level index includes low risk, medium risk, and high risk;

[0046] Step 3: Build a new business form public security risk prediction model based on a deep learning network, with the feature index as the input and the public security management risk level index as the output. Divide the historical public security feature data in the past three years into public security feature data for each three months on average, and train the model based on the feature index related to the new business form and the public security management risk level index for each three months. Input the public security feature index related to the new business form within the current three months into the model to obtain the public security management risk level index;

[0047] Step 4: Establish a feedback mechanism in the public security computer system to obtain the feedback data of the current new business form users on the open management of the new business form public security. The feedback data includes the total number of reported public security incidents, the user satisfaction score, and the public security incident resolution rate. Generate a feedback adjustment factor based on the feedback data of the new business form users, and use the obtained feedback adjustment factor to combine with the public security feature index related to the new business form within the current three months to comprehensively generate a public security management risk correction coefficient;

[0048] Step 5: Set the upper and lower limits of the threshold management interval, compare the comprehensively generated public security management risk correction coefficient with the threshold management interval, and determine whether to upgrade or downgrade the public security management risk level index output by the model to determine the final public security management risk level index, and set corresponding security response measures according to different public security management risk level indexes.

[0049] The present invention also provides a new business form public security open management comprehensive service device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it realizes the steps of the above new business form public security open management comprehensive service method.

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] The present invention effectively integrates historical public security feature data related to new business forms and user feedback by establishing a comprehensive service system for open management of public security in new business forms, forming a dynamic and intelligent public security management mechanism. Through in-depth analysis of historical data and calculation of feature indices, it can accurately evaluate the public security situation and management risk levels. Such a system not only improves the ability to identify emerging businesses and their potential risks but also enhances the response efficiency of public security incidents, making management decisions more scientific and reasonable.

[0052] In addition, the public security risk prediction model constructed by the present invention using deep learning technology can analyze and predict current public security features in real time, thereby providing timely and accurate decision-making support for public security departments. By establishing a user feedback mechanism, the system can dynamically adjust management strategies to adapt to the changing public security environment. This efficient feedback adjustment mechanism not only enhances users' sense of security and satisfaction but also promotes the transparency and trust of public security management, creating a good public security atmosphere for the healthy development of new business forms. Brief Description of the Drawings

[0053] Figure 1 It is a schematic diagram of the system module process of the present invention.

[0054] Figure 2 It is a schematic diagram of the overall method process of the present invention. Detailed Embodiments

[0055] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with specific embodiments.

[0056] It should be noted that unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The "first", "second", and similar terms used in the present invention do not indicate any order, quantity, or importance, but are only used to distinguish different components. Words such as "including" or "comprising" mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connected" or "linked" are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. "Upper", "lower", "left", "right", etc. are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0057] Embodiment:

[0058] Please refer to Figure 1 The present invention provides a technical solution:

[0059] A new business form public security open management integrated service system, and the specific steps include:

[0060] A data collection and prediction module, which is used to obtain historical public security feature data related to the new business form within multiple past historical time periods through the public security computer system. The historical public security feature data includes the total number of business transaction activities related to the new business form, the total number of public security incidents, the number of similar public security incidents, the total number of negative comments, the total number of comments, the average response time of public security incidents, and the area of the region under public security management, and predict the public security feature data related to the new business form within the current three months based on the public security computer system;

[0061] A feature index calculation module, which calculates and generates a feature index used to represent the public security status of the new business form based on the obtained historical public security feature data. The feature index includes a public security incident occurrence index, a social media crisis index, a public security response efficiency index, a recurrence rate index, and a public security incident location density index, and scores the feature index related to the new business form in the past three years based on the historical public security data of the new business form in the public security system to determine its public security management risk level index. The public security management risk level index includes low risk, medium risk, and high risk;

[0062] A public security risk prediction model module, which constructs a new business form public security risk prediction model with the feature index as the input and the public security management risk level index as the output based on a deep learning network, divides the historical public security feature data in the past three years, evenly divides it into public security feature data for each three months, and conducts model training based on the feature index related to the new business form and the public security management risk level index for each three months, and inputs the public security feature index related to the new business form within the current three months into the model to obtain the public security management risk level index;

[0063] A user feedback mechanism module, which is used to establish a feedback mechanism in the public security computer system, obtain feedback data from current new business form users on the public security open management of the new business form. The feedback data includes the total number of public security incident reports, user satisfaction scores, and the resolution rate of public security incidents, generates a feedback adjustment factor based on the feedback data of the new business form users, and comprehensively generates a public security management risk correction coefficient by combining the obtained feedback adjustment factor with the public security feature index related to the new business form within the current three months;

[0064] A risk level decision-making module, which is used to set the upper and lower limits of the threshold management range, compare the comprehensively generated public security management risk correction coefficient with the threshold management range, determine whether to upgrade or downgrade the public security management risk level index output by the model, so as to determine the final public security management risk level index, and set corresponding security response measures according to different public security management risk level indexes.

[0065] It should be noted that by quantifying the public security incident occurrence index, social media crisis index, public security response efficiency index, recurrence rate index and public security incident location density index, the public security risks faced by the new business format can be analyzed comprehensively and systematically. These indexes not only provide intuitive data support for the public security department to help it identify potential security hazards and problems, but also provide a basis for formulating scientific public security management strategies and optimizing resource allocation, so as to improve the efficiency and effectiveness of overall public security management and ultimately ensure social security and stability.

[0066] Therefore, it is necessary to calculate and generate a characteristic index for characterizing the public security situation of the new business format based on the obtained historical public security characteristic data. The method is as follows:

[0067] Calculate the public security incident occurrence index based on the total number of business transaction activities and the total number of public security incidents in the public security-related characteristic data of the new business format. The formula is as follows:

[0068]

[0069] Among them, represents the public security incident occurrence index, and are the total number of public security incidents and the total number of business transaction activities respectively; in the above formula, when becomes larger, it will cause to increase, which means that the total number of public security incidents increases and the potential security hazards increase; while when increases, it will cause to decrease, indicating that the transaction activities of the new business format increase, the overall management environment security is improved, and the potential transaction risks are reduced; The smaller it is, the better, indicating that in a certain number of business transaction activities, the incidence of public security incidents is relatively low, which usually means that the public security management is proper and the sense of security of the public and businesses is relatively high.

[0070] Calculate the social media crisis index based on the total number of negative comments and the total number of comments in the public security-related characteristic data of the new business format. The formula is as follows:

[0071]

[0072] Among them, represents the social media crisis index, and represent the total number of negative comments and the total number of comments respectively; in the above formula, represents the total number of negative comments increases, which will lead to an increase in the social media crisis index because among the feedback from all users, comments expressing dissatisfaction or negative emotions occupy a larger share, reflecting the public's dissatisfaction with public security management and also indicating that there are relatively large risks in public security management; The smaller it is, the better, indicating that positive or neutral comments occupy a larger proportion in the users' feedback. This usually shows that the public is satisfied with the measures and effects of public security management and believes that public security management can effectively guarantee their safety.

[0073] Calculate the public security response efficiency index based on the average response time of public security incidents and the total number of public security incidents in the data of the characteristics related to public security in the new business form. The formula is:

[0074]

[0075] Among them, represents the public security response efficiency index, is the average response time of public security incidents; in the above formula, decreases, which will lead to an increase because when the average response time of public security incidents decreases, it means that the public security department can respond and handle public security incidents faster, and this rapid response improves the overall response efficiency; decreases, which will also make increase because the decrease in the total number of public security incidents is related to the improvement of the monitoring and early warning mechanism by the public security department, which means that potential public security incidents can be identified and processed faster, reflecting the improvement of the overall governance ability; therefore, the larger it is, the better, indicating that when the processing speed of public security incidents accelerates, it means that resources such as police force and equipment can be effectively utilized in a shorter time, so that when facing more public security incidents, the relevant departments can allocate and handle them more flexibly and efficiently.

[0076] Calculate the recurrence rate index based on the number of similar public security incidents and the total number of public security incidents in the data of the characteristics related to public security in the new business form. The formula is:

[0077]

[0078] Among them, represents the recurrence rate index, is the number of similar public security incidents; in the above formula, the increase of will lead to The increase is due to the higher frequency of similar events occurring repeatedly, which means that public security management has failed to effectively prevent the recurrence of events in some aspects, reflecting potential deficiencies in management or preventive measures; therefore should be as small as possible because The smaller it is, the fewer public security incidents of the same type occur. This helps enhance the public's sense of security and trust in the public security management department. The public will feel that the living environment is safer, strengthening their confidence in social security.

[0079] Calculate the location density index of public security incidents based on the total number of public security incidents and the area of public security management in the relevant characteristic data of new business forms of public security. The formula used is:

[0080]

[0081] Wherein, represents the location density index of public security incidents, is the area of public security management; in the above formula, An increase in will lead to an increase because in a fixed area of public security management, the more, the higher the frequency of public security incidents in this area. The increase in the location density index of public security incidents will reduce the public's sense of security. Residents may feel that this area is not safe enough, thus affecting their living and working conditions. Therefore should be as small as possible.

[0082] It should be noted that the new business form public security risk prediction model constructed based on the deep learning network can effectively identify and capture complex public security characteristic relationships by inputting feature indices and undergoing multiple convolutional and non-linear processes, thus accurately predicting the public security management risk level. The establishment of this model not only improves the scientificity and accuracy of public security management, but also provides timely and effective decision-making support for relevant departments, helping to proactively identify and respond to potential public security risks in a dynamically changing social environment, thereby enhancing public safety and social stability.

[0083] Therefore, it is necessary to construct a new business form public security risk prediction model based on the deep learning network with feature indices as the input and public security management risk level indicators as the output. The method used is:

[0084] The new business form public security risk prediction model adopts a neural network convolutional structure, including an input layer, a hidden layer, and an output layer. The input layer is responsible for receiving the feature indices that represent the public security status of the new business form after extraction; the hidden layer is used to process the extracted feature indices. By applying multiple convolutional kernels and using the ReLU activation function, a non-linear relationship is introduced to enable the model to fit complex feature relationships; an independent neuron is set in the output layer, which is responsible for converting the feature index representation extracted by the hidden layer into the final prediction result, that is, outputting the public security management risk level index;

[0085] Obtain the feature indices related to the new business form in the past three years, and divide the public security feature data in the past three years into public security feature data for each three months. Use the public security computer system to evaluate and score, and set the public security management risk level indicators including mild indicators, moderate indicators, and severe indicators. Use the feature indices related to the new business form and the public security management risk level indicators for each three months in the past three years to train the model. During the training process, select the mean square error function as the loss function, calculate the loss function value based on the output result and the true label, and calculate the gradient through the backpropagation algorithm to update the weights and biases of the neural network. Repeat the above operations until the model reaches the predetermined number of training rounds, and the number of training rounds is set to 50 - 100 times.

[0086] It should be noted that generating the public security management risk factor based on the feedback data of new business form users and comprehensively generating the public security management risk correction coefficient in combination with relevant public security feature indices is important because it can dynamically reflect the true feelings and feedback of users on public security management, thus making the risk assessment more accurate and timely. By introducing indicators such as the number of reports, user satisfaction, and incident resolution rate, the feedback adjustment factor can effectively adjust the risk assessment to make the management measures more in line with actual needs. In addition, using the comprehensive method of weighted feature indices ensures that the relative impacts of different factors on risk assessment are reasonably reflected, increasing the flexibility and response ability of the system to better adapt to the complex and changeable public security environment under the new business form.

[0087] Therefore, it is necessary to generate the public security management risk factor based on the feedback data of new business form users, and use the obtained public security management risk factor to comprehensively generate the public security management risk correction coefficient in combination with the public security feature indices related to the new business form within the current three months. The method is as follows:

[0088] Obtain the feedback data of users on the open management of new business form public security, including the total number of reports of public security incidents, user satisfaction scores, and the resolution rate of public security incidents. Calculate the feedback adjustment factor based on the feedback data of the open management of new business form public security. The formula is as follows:

[0089]

[0090] Among them, represents the feedback adjustment factor, is the total number of reports on public security incidents, is the user satisfaction score, and , with a full score of ten points, is the resolution rate of public security incidents. The resolution rate of public security incidents is the ratio of the total number of resolved public security incidents to the total number of public security incidents; in the above formula, the higher the score of, the greater the feedback adjustment factor, indicating that users are relatively satisfied with the public security management of the new business format, and also reflecting that the potential safety hazards of public security management are relatively small; the larger, will also cause to increase, because the increase of means that the proportion of the number of public security incidents handled and resolved in the total number of incidents has increased, indicating that the management department has strong response and handling capabilities for public security incidents, effectively reducing the number of unresolved incidents, which further enhances users' trust and satisfaction in public security management; the decrease of will cause to increase, because when there are relatively few reports, the ratio of satisfaction and resolution rate increases, which means that users still have a relatively high satisfaction with public security management in the case of relatively few reports of public security incidents, enhancing users' sense of trust; therefore, the feedback adjustment factor the larger the better, indicating that the performance of public security management in user feedback is more positive, which helps to more accurately adjust the public security risk assessment and optimize the current management strategy.

[0091] The public security management risk correction coefficient is comprehensively generated based on the calculated public security management risk factor and the characteristic index representing the public security status of the new business format. The formula is as follows:

[0092]

[0093] Among them, represents the public security management risk correction coefficient, , , , , are the weight ratios of their respective corresponding characteristic indexes, and ; in the above formula, , , , the decrease of will all cause The decrease in the risk of public security management indicates that the public security environment has improved, the response efficiency has increased, the participation of social management has increased, and the public's trust in public security management has increased. The decrease in these factors collectively points to the improvement of the effectiveness of public security management, thereby reducing the public security management risk correction coefficient, which means that the overall risk level of public security management is decreasing; , The increase will also lead to The decrease of and the increase of feedback adjustment factor means that users' satisfaction with public security management is improved and the resolution rate of public security incidents is improved, indicating that the management department's ability to respond to and handle public security incidents is increasing. The increase in means the overall improvement of the public security environment, including the improvement of social security conditions, the improvement of the effectiveness of public security management measures, and the increase in users' trust in the public security environment; therefore The smaller the better. On the one hand, it shows that the effectiveness of public security management is increasing, which means that the overall risk level of public security management is decreasing. On the other hand, it shows that the user's satisfaction and sense of security are improving. It means that when the public feels that public security management is more effective and the public security environment is safer, the public security management risk correction coefficient will decrease accordingly, reflecting the improvement of comprehensive governance effects and the reduction of potential risks. The reason why the weight ratio is set to First, in order to prevent negative values, all weight ratios must be greater than 0. The corresponding weight ratio The reason why it is set to the maximum is that the public security incident index is an important indicator that directly reflects the public security situation, and its change has the most significant impact on the public security management risk correction coefficient. The larger the value, the higher the frequency of public security incidents, which directly leads to an increase in public security management risks. The largest weight ratio; recurrence rate index It indicates the frequency of recurrence of the same type of public security incidents. A high recurrence rate usually means that public security management measures have failed to effectively prevent the recurrence of the same type of incidents. The second largest weight ratio: Public security incident response efficiency index It measures the speed at which the public security department responds to public security incidents. Although it has an important impact on public security risks, it is , Its impact is indirect. Faster response time usually means timely handling of the incident, which helps reduce subsequent risks. The third largest weight ratio; and the public security incident location density index The lower weight is given because Indicates the occurrence frequency of public security incidents within a specific area. Although it provides useful information about the regional security situation, compared to other indicators, its direct impact on the overall public security management risk is relatively small. Therefore, setting a lower weight reflects its secondary role in influencing public sense of security and public security risk assessment; The social media crisis index is given the lowest weight ratio because mainly reflects users' feedback on public security management. The increase in negative comments may affect the public's perception of the security environment. Although the feedback information is important for the improvement of public security management, it is still a relatively indirect indicator and more of a reflection of potential problems. Therefore, it is appropriate to assign it the lowest weight to highlight its auxiliary role in public security management risk assessment.

[0094] It should be noted that by setting a threshold management range and combining the generated public security management risk correction coefficient, the current public security risk level can be systematically evaluated and reflected. If it is within the normal range, it indicates that the public security situation is stable and no management measures need to be adjusted; while when it exceeds the set threshold, timely risk escalation or de-escalation processing can effectively respond to potential public security threats and ensure social security. In addition, setting special processing conditions to ensure stability in the case of mild and severe risks further enhances the flexibility and accuracy of management, ensuring the public's sense of security and trust. Such a risk management mechanism not only improves the scientific nature and pertinence of public security management, but also provides an important basis for policy formulation, thus promoting social harmony and stability.

[0095] Therefore, it is necessary to determine the final public security management risk level indicators, and the method is as follows:

[0096] Set the upper and lower limits of the threshold management range , the public security management risk level indicators output by the model include mild risk, medium risk and severe risk. The generated public security management risk correction coefficient is compared with the upper and lower limits of the threshold management range. If , it indicates that no upgrading or downgrading treatment is required, and the level indicator output by the model is the final public security management risk level indicator; if , it indicates that upgrading treatment is required, and the level indicator output by the model is upgraded by one level as the final public security management risk level indicator; if , it indicates that downgrading treatment is required, and the level indicator output by the model is downgraded by one level as the final public security management risk level indicator; Set limiting conditions for the level indicator output by the model: when the public security management risk level indicator output by the model is mild risk, no downgrading treatment is required at this time; when the public security management risk level indicator output by the model is severe risk, no upgrading treatment is required at this time.

[0097] It should be noted that according to the final public security management risk level indicators output by the new business format public security risk prediction model, different corresponding security response measures are formulated respectively, including: when the final public security management risk level indicator output by the model is a low risk, the public security department can carry out community publicity activities to enhance the safety awareness and prevention ability of residents, increase the patrol frequency, strengthen public security inspections, ensure the visibility of police officers in key areas, and can also provide online consultation and reporting channels to encourage residents to report suspicious activities; when the final public security management risk level indicator output by the model is a medium risk, the public security department can strengthen public security monitoring, add surveillance cameras and alarm systems in high-risk areas, organize community safety meetings, invite residents to participate, and jointly discuss safety countermeasures. Finally, additional police forces can be dispatched to strengthen the key attention and rapid response to public security incidents prone to occur; when the final public security management risk level indicator output by the model is a high risk, the public security department should immediately pay attention, activate the emergency plan, dispatch special police or reinforcement forces to high-risk areas to improve the response ability, and implement temporary closures or restricted access to specific areas to ensure the safety of residents. Finally, strengthen cooperation with social service agencies to provide psychological counseling and support services to help affected residents regain a sense of security.

[0098] Please refer to Figure 2 , the present invention also provides a new business format public security open management comprehensive service method, and the comprehensive service method is used to execute the above-mentioned new business format public security open management comprehensive service system, including:

[0099] Step 1: Obtain historical public security feature data related to the new business format in multiple past historical time periods through the public security computer system. The historical public security feature data includes the total number of business transaction activities related to the new business format, the total number of public security incidents, the number of similar public security incidents, the total number of negative comments, the total number of comments, the average response time of public security incidents, and the area of public security management, and predict the public security feature data related to the new business format within the current three months based on the public security computer system;

[0100] Step 2: Calculate and generate a feature index for characterizing the public security status of the new business format based on the obtained historical public security feature data. The feature index includes a public security incident occurrence index, a social media crisis index, a public security response efficiency index, a recurrence rate index, and a public security incident location density index, and score the feature index related to the new business format in the past three years based on the historical new business format public security data of the public security system to determine its public security management risk level indicator. The public security management risk level indicator includes low risk, medium risk, and high risk;

[0101] Step 3: Based on a deep learning network, construct a new business form public security risk prediction model with the feature index as the input and the public security management risk level index as the output. Divide the historical public security feature data of the past three years, and evenly divide it into public security feature data for each three months. Then, based on the feature index related to the new business form and the public security management risk level index for each three months, conduct model training. Input the public security feature index related to the new business form within the current three months into the model to obtain the public security management risk level index;

[0102] Step 4: Establish a feedback mechanism in the public security computer system to obtain the feedback data of current new business form users on the open management of new business form public security. The feedback data includes the total number of reported public security incidents, user satisfaction ratings, and the resolution rate of public security incidents. Generate a feedback adjustment factor based on the feedback data of new business form users, and use the obtained feedback adjustment factor to comprehensively generate a public security management risk correction coefficient in combination with the public security feature index related to the new business form within the current three months;

[0103] Step 5: Set the upper and lower limits of the threshold management interval. Compare the comprehensively generated public security management risk correction coefficient with the threshold management interval to determine whether to upgrade or downgrade the public security management risk level index output by the model, so as to determine the final public security management risk level index, and set corresponding security response measures according to different public security management risk level indexes.

[0104] The present invention further provides a comprehensive service device for the open management of new business form public security. The device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the above-mentioned comprehensive service method for the open management of new business form public security.

[0105] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain a formula that is closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0106] The above embodiments can be implemented in whole or in part through software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented through electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0107] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit. It may be located in one place or distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] As described above, the above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application.

Claims

1. A new type of public security open management integrated service system, characterized by: The specific steps include: A data collection and prediction module, the data collection and prediction module is used to obtain historical public security characteristic data related to the new business format in multiple historical time periods through the public security computer system, the historical public security characteristic data includes the total number of business transaction activities related to the new business format, the total number of public security incidents, the number of similar public security incidents, the total number of negative comments, the total number of comments, the average response time of public security incidents and the area of ​​public security management, and predict the public security characteristic data related to the new business format within the current three months based on the public security computer system; A characteristic index calculation module, wherein the characteristic index calculation module calculates and generates characteristic indexes for characterizing the public security status of new business formats based on the acquired historical public security characteristic data, wherein the characteristic indexes include a public security incident occurrence index, a social media crisis index, a public security response efficiency index, a recurrence rate index, and a public security incident location density index, and scores characteristic indexes related to new business formats in the past three years based on the historical public security data of new business formats in the public security system to determine their public security management risk level indicators, wherein the public security management risk level indicators include mild risk, moderate risk, and severe risk; A public security risk prediction model module, wherein the public security risk prediction model module constructs a new business format public security risk prediction model based on a deep learning network, with a feature index as input and a public security management risk level index as output, divides the historical public security feature data of the past three years into public security feature data for every three months on average, and performs model training based on the feature index and public security management risk level index related to the new business format every three months, and inputs the public security feature index related to the new business format within the current three months into the model to obtain the public security management risk level index; A user feedback mechanism module, which is used to establish a feedback mechanism in the public security computer system, obtain feedback data from current new business users on the public security open management of new business forms, the feedback data includes the total number of public security incident reports, user satisfaction scores and public security incident resolution rates, generate feedback adjustment factors based on the feedback data of new business users, and use the obtained feedback adjustment factors combined with the public security characteristic index related to the new business form within the current three months to comprehensively generate a public security management risk correction coefficient; The risk level decision module is used to establish the upper and lower limits of the threshold management interval, compare the comprehensively generated public security management risk correction coefficient with the threshold management interval, determine whether to upgrade or downgrade the public security management risk level indicator output by the model, so as to determine the final public security management risk level indicator, and set corresponding security response measures according to different public security management risk level indicators.

2. According to claim 1, a new business form public security open management comprehensive service system is characterized by: Based on the historical public security characteristic data obtained, the characteristic index used to characterize the public security status of the new business format is calculated and generated. The method is as follows: The public security incident index is calculated based on the total number of business transaction activities and the total number of public security incidents in the new business model public security-related characteristic data. The formula is: in, It indicates the index of public security incidents. , They are the total number of public security incidents and the total number of business transaction activities; The social media crisis index is calculated based on the total number of negative comments and total number of comments in the new business security-related characteristic data. The formula is as follows: in, represents the social media crisis index, , Represents the total number of negative comments and the total number of comments respectively; The public security response efficiency index is calculated based on the average response time of public security incidents and the total number of public security incidents in the new business model public security-related characteristic data. The formula is: in, represents the public security response efficiency index, The average response time for public security incidents; The recurrence rate index is calculated based on the number of similar public security incidents and the total number of public security incidents in the new business security-related characteristic data. The formula is: in, represents the recurrence rate index, The number of similar public security incidents; The public security incident location density index is calculated based on the total number of public security incidents and the area of ​​public security management in the new business model public security-related characteristic data. The formula is: in, represents the location density index of public security incidents, The area for public security management.

3. According to claim 1, a new business form public security open management comprehensive service system is characterized in that: A new business security risk prediction model is constructed based on a deep learning network with feature index as input and public security management risk level index as output. The method is as follows: The new business format public security risk prediction model adopts a neural network convolution structure, including an input layer, a hidden layer and an output layer. The input layer is responsible for receiving the extracted feature index that characterizes the public security status of the new business format; the hidden layer is used to process the extracted feature index. By applying multiple convolution kernels and using the ReLU activation function, nonlinear relationships are introduced to enable the model to fit complex feature relationships; an independent neuron is set in the output layer, which is responsible for converting the feature index representation extracted by the hidden layer into the final prediction result, that is, outputting the public security management risk level indicator.

4. According to claim 2, a new business form public security open management comprehensive service system is characterized by: The public security management risk factor is generated based on the feedback data of new business users. The public security management risk factor is combined with the public security characteristic index related to the new business within the current three months to comprehensively generate the public security management risk correction coefficient. The method is based on: The feedback data of users on the new business form of public security open management is obtained, including the total number of public security incident reports, user satisfaction scores, and public security incident resolution rates. The feedback adjustment factor is calculated based on the feedback data of the new business form of public security open management. The formula is as follows: in, represents the feedback regulation factor, The total number of reports of public security incidents, Rate user satisfaction, and , using a full score system of 10. The resolution rate of public security incidents is It is the ratio of the total number of resolved public security incidents to the total number of public security incidents; The public security management risk correction coefficient is generated based on the calculated public security management risk factor combined with the characteristic index representing the public security situation of the new business format. The formula is: in, represents the public security management risk correction coefficient, , , , , are the weight ratios of their corresponding characteristic indexes, and .

5. According to claim 1, a new business form public security open management comprehensive service system is characterized by: The final public security management risk level indicator is determined based on the following method: Set the upper and lower limits of the threshold management interval The public security management risk level indicators output by the model include mild risk, moderate risk and severe risk. The public security management risk correction coefficient generated Compare with the upper and lower limits of the threshold management interval. , it indicates that no upgrading or downgrading is required, and the level index output by the model is the final public security management risk level index; if , it indicates that an upgrade is needed, and the level index output by the model is raised to one level as the final public security management risk level index; if , it indicates that downgrading is required, and the level index output by the model is reduced by one level as the final public security management risk level index; limiting conditions are set for the model output level index: when the public security management risk level index output by the model is a mild risk, there is no need to downgrade it; when the public security management risk level index output by the model is a severe risk, there is no need to upgrade it.

6. A new business model public security open management comprehensive service method, characterized in that: The comprehensive service method is used to implement a new business open security management comprehensive service system as described in any one of claims 1 to 5, comprising: Step 1: Obtain historical public security characteristic data related to the new business format in multiple historical time periods through the public security computer system, wherein the historical public security characteristic data includes the total number of business transaction activities related to the new business format, the total number of public security incidents, the number of similar public security incidents, the total number of negative comments, the total number of comments, the average response time of public security incidents, and the area of ​​public security management, and make a prediction of the public security characteristic data related to the new business format within the current three months based on the public security computer system; Step 2: Based on the historical public security characteristic data obtained, characteristic indexes are calculated to characterize the public security status of new business formats, including the public security incident occurrence index, social media crisis index, public security response efficiency index, recurrence rate index, and public security incident location density index. Based on the historical public security data of new business formats in the public security system, characteristic indexes related to new business formats in the past three years are scored to determine their public security management risk level indicators, which include mild risk, moderate risk, and severe risk. Step 3: Based on the deep learning network, a new business format public security risk prediction model is constructed with the input as the characteristic index and the output as the public security management risk level index. The historical public security characteristic data of the past three years are divided and evenly divided into public security characteristic data every three months. The model is trained based on the characteristic index related to the new business format and the public security management risk level index every three months. The public security characteristic index related to the new business format in the current three months is input into the model to obtain the public security management risk level index; Step 4: Establish a feedback mechanism in the public security computer system to obtain feedback data from current new business form users on the public security open management of new business forms, including the total number of public security incident reports, user satisfaction scores, and public security incident resolution rates. Generate a feedback adjustment factor based on the feedback data from new business form users, and use the obtained feedback adjustment factor combined with the public security characteristic index related to the new business form within the current three months to comprehensively generate a public security management risk correction coefficient; Step 5: Set the upper and lower limits of the threshold management interval, compare the comprehensively generated public security management risk correction coefficient with the threshold management interval, determine whether to upgrade or downgrade the public security management risk level indicator output by the model, so as to determine the final public security management risk level indicator, and set corresponding security response measures according to different public security management risk level indicators.

7. A new type of public security open management comprehensive service device, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the new business model public security open management comprehensive service method as described in claim 6 are implemented.

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