Disabled person subsidy management and control system based on big data analysis

Abstract

The invention relates to the technical field of information processing, in particular to a disabled person subsidy management and control system based on big data analysis, and is used for solving the problems that user requirements cannot be comprehensively evaluated from multiple angles, priorities cannot be reasonably sorted, and resource allocation and service decision cannot be effectively supported in the prior art. According to the invention, objective, accurate and real-time analysis is carried out through the demand evaluation module by using user historical data, subjective deviation is avoided, fairness and timeliness of an evaluation result are ensured, user demands are comprehensively evaluated from multiple angles, demand characteristics are identified, a basis is provided for service optimization and extension, a demand urgency coefficient is calculated by adopting a formulation method, and the demand evaluation efficiency is improved. And the priorities are divided according to percentiles, so that the scientificity and reasonability of sorting are ensured, and resource allocation and service decision are effectively supported.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and more specifically, to a disability subsidy management and control system based on big data analysis. Background Art

[0002] With the development of social economy, the government and society are increasingly caring about the disabled, and the disability subsidy policy has been continuously improved. However, in actual operation, the lack of effective management and monitoring methods has led to problems such as inaccurate subsidy distribution and inefficient use of funds. The traditional subsidy management system mostly relies on manual review, which is not only time-consuming and labor-intensive, but also difficult to ensure fairness and justice.

[0003] The patent application with reference publication number CN118469730A discloses a system and method for calculating subsidies for the disabled based on electronic receipts, including screening out target electronic receipts, extracting project names and project amounts from project information, comparing and reviewing project names with standard names, identifying target names and target amounts, calculating the total subsidy amount, and determining whether the total subsidy amount exceeds the standard subsidy range, marking abnormal amounts from the target amount, and generating the total subsidy amount after review; compared with the prior art, the extraction and identification range of project names and project amounts can be narrowed, and by independently calculating and analyzing the over-limit state and over-limit ratio of the total subsidy amount, the true value of the amount of subsidy required to be provided to the disabled can be truly determined, thereby avoiding the phenomenon of over-subsidy and under-subsidy, and improving the efficiency and accuracy of the calculation of subsidies for the disabled, greatly reducing the probability of errors in subsidy calculation; However, existing technologies can intelligently screen electronic receipts, accurately extract project information, calculate the total amount of subsidies, and automatically handle abnormal amounts to ensure that people with disabilities receive reasonable and accurate subsidies. However, they are unable to comprehensively assess user needs from multiple angles, cannot reasonably sort priorities, cannot effectively support resource allocation and service decisions, cannot accurately assess user economic conditions, and cannot accurately calculate subsidy amounts based on demand priorities, economic conditions, and regional differences. This reduces the efficiency and accuracy of subsidy calculations and is inconvenient for the review and issuance of subsidy amounts.

[0004] To this end, we propose a disability subsidy management and control system based on big data analysis to address the above issues. Summary of the invention

[0005] The purpose of the present invention is to provide a disability subsidy management and control system based on big data analysis, which solves the problems that the prior art intelligently screens electronic receipts, accurately extracts project information, calculates the total subsidy amount, automatically handles abnormal amounts, and ensures that disabled people obtain reasonable and accurate subsidies, but is unable to comprehensively evaluate user needs from multiple angles, cannot reasonably sort priorities, cannot effectively support resource allocation and service decisions, cannot accurately evaluate user economic conditions, and cannot accurately calculate the subsidy amount based on demand priorities, economic conditions and regional differences, which reduces the efficiency and accuracy of the subsidy calculation and is inconvenient for the review and issuance of the subsidy amount.

[0006] The purpose of the present invention is achieved through the following technical solutions: A disability subsidy management and control system based on big data analysis, including a management and control platform, a user information collection module, a qualification review module, a demand assessment module, an economic situation analysis module, and a subsidy amount calculation module; User information collection module, used to provide application forms, support input of basic information and upload of relevant certification materials, and automatically connect to the database to obtain and integrate user history records; The qualification review module is used to check the completeness of application materials, confirm necessary information, automatically review user information according to standards, and confirm application qualifications; Demand assessment module, which is used to obtain historical data and statistical information, evaluate user needs, consumption habits and service usage records, and prioritize user needs according to urgency; The economic status analysis module is used to obtain the user's monthly income, daily expenses and family assets information, generate the user's income and expenditure report, and comprehensively evaluate the user's economic status; The subsidy amount calculation module is used to calculate the subsidy amount based on demand priority, economic status assessment and regional differences, generate calculation results and basis, and recommend them to reviewers for review.

[0007] As a preferred embodiment of the present invention, the specific process of the user information collection module supporting application form filling, certification material uploading and user history record integration is as follows: When filling out the application form, users need to fill in basic information, including name, ID number, gender, age, disability type, payment account, contact information, residential address, date of birth, family size, and source of income. Users are guided to provide valid information through input boxes and drop-down menus; When uploading supporting documents, users need to upload supporting documents, including valid identity documents, income documents, residence documents, and medical or care needs documents. All uploaded documents must be in PDF, JPEG, or PNG format, and the size limit for each file is 5MB. All uploaded supporting documents will be automatically formatted. When integrating user historical records, the database is connected through a connection tool to automatically pull user historical records. User historical records include application history, subsidy collection record, social service record and credit record. Application history includes the user's past application status, application amount and application date. Subsidy collection record includes the type of subsidy and subsidy amount received by the user. Social service record includes the user's use of social services. Credit record includes the user's credit score and loan record. The pulled user historical records are cleaned and standardized, and the cleaned and standardized user historical records are integrated to form a comprehensive user historical record archive.

[0008] As a preferred embodiment of the present invention, the specific process of the qualification review module checking the application materials and reviewing the user information is as follows: The system will check the completeness of the application materials through input verification, file upload verification and database consistency check; The system will confirm the necessary information, including basic identity information, contact information, financial status and residence information. The system will compare the information filled in by the user with the list of necessary information; The system will automatically review user information according to the set review standards, compare the user's information with the standards, and come up with the final review results. Users who meet all the standards will be marked as "eligible" and enter the subsequent process. Users who do not meet the standards will be marked as "ineligible" and will receive specific reasons and improvement suggestions provided by the system; The system will integrate all review results, generate a detailed review report, and notify the applicant of the final review results, including whether they meet the qualifications and the reasons.

[0009] As a preferred embodiment of the present invention, the specific process of the demand assessment module assessing user needs, consumption habits and service usage records is as follows: Obtain and organize historical data and statistical information, including basic user information, consumption records, service usage records, and historical subsidy information; By analyzing the user's consumption records and service usage records, the user's demand characteristics can be extracted, including the following demand characteristics: consumption frequency, consumption amount and service usage frequency. The consumption frequency refers to the number of times the user consumes per unit time, the consumption amount refers to the total consumption amount of the user in a specific time period, and the service usage frequency refers to the number of times the user applies for subsidies or services in a specific time period. The user's consumption habits and service usage records are evaluated through two indicators: income consumption ratio and service utilization rate. The income consumption ratio refers to the ratio of the user's total consumption expenditure in a specific time period to his / her income in the same period. The service utilization rate refers to the ratio of the number of services actually used by the user in a specific time period to the total number of optional services.

[0010] As a preferred implementation of the present invention, the specific process of the demand assessment module prioritizing user demands is as follows: Obtain the user's income consumption ratio and service utilization rate in multiple time periods, and sum and average them to obtain the average income consumption ratio PSX and average service utilization rate PFS. Obtain the demand urgency coefficient, where b1 and b2 are both preset proportional factor coefficients and b2>b1>0; The calculated demand urgency coefficient XJ values ​​are sorted from small to large and divided into different demand priorities according to percentiles. The top 20% XJ values ​​correspond to urgent demands, 20%-60% XJ values ​​correspond to high-priority demands, 60%-80% XJ values ​​correspond to medium-priority demands, and the bottom 20% XJ values ​​correspond to low-priority demands.

[0011] As a preferred embodiment of the present invention, the specific process of the economic situation analysis module generating an income and expenditure report and evaluating the economic situation is as follows: Obtain and organize the user's monthly income, daily expenditure and family asset information, and generate an income and expenditure report, which includes personal information, income, expenditure and assets; The user's economic situation is assessed using three indicators: income-to-expenditure ratio, net asset ratio, and debt ratio. The income-to-expenditure ratio refers to the ratio of all income earned by the user in a specific period of time to the user's daily expenses incurred in a specific month. The net asset ratio refers to the ratio of all assets owned by the user's family to all income earned by the user in a specific month. The debt ratio refers to the ratio of all debts of the user's family to all assets owned by the user's family.

[0012] As a preferred embodiment of the present invention, the income-expenditure ratio, net asset ratio and debt ratio of the user in multiple months are obtained, and the average income-expenditure ratio PSZ, average net asset ratio PJZ and average debt ratio PFZ are obtained by summing them up and averaging them respectively. The economic status assessment coefficient is obtained, where c1, c2, and c3 are all preset proportional factor coefficients, and c1, c2, and c3 are all greater than 0. The economic status assessment coefficient JZP is compared and analyzed with the preset economic status assessment coefficient threshold: If the economic status assessment coefficient JZP is greater than the preset economic status assessment coefficient threshold, it indicates that the user's economic status is good; If the economic status assessment coefficient JZP is less than or equal to the preset economic status assessment coefficient threshold, it indicates that the user's economic status is poor.

[0013] As a preferred implementation of the present invention, the specific process of the subsidy amount calculation module calculating the subsidy amount is as follows: Obtain the user's demand priority and convert the demand priority into a demand priority adjustment coefficient. The specific values ​​of the demand priority adjustment coefficient are as follows: The demand priority adjustment factor corresponding to urgent demand is 1.2; The demand priority adjustment coefficient corresponding to the high priority demand is 1.0; The demand priority adjustment coefficient corresponding to the medium priority demand is 0.8; The demand priority adjustment coefficient corresponding to the low priority demand is 0.6; The initial subsidy amount is obtained by multiplying the converted need priority adjustment coefficient by the basic subsidy amount. The basic subsidy amount is set according to the disability category and relevant standards.

[0014] As a preferred implementation of the present invention, the economic status assessment result of the user is obtained to determine the economic status adjustment coefficient. The specific value of the economic status adjustment coefficient is as follows: The economic adjustment coefficient corresponding to a user with good economic conditions is 0.7; The economic adjustment coefficient corresponding to the poor economic situation of users is 1.2; The second stage subsidy amount is obtained by multiplying the determined economic situation adjustment factor by the initial subsidy amount; The regional difference coefficient is determined according to the user's residential area. The specific values ​​of the regional difference coefficient are as follows: The regional variation coefficient corresponding to economically developed regions is 0.8; The regional variation coefficient corresponding to the economically average region is 1.0; The regional variation coefficient corresponding to the economically underdeveloped regions is 1.2; Multiply the determined regional difference coefficient by the second-stage subsidy amount to obtain the final subsidy amount.

[0015] As a preferred implementation mode of the present invention, the calculation result and the calculation basis are automatically generated after the calculation is completed. The generated calculation result is the final subsidy amount. The calculation basis is the calculation parameters. The calculation parameters include the basic subsidy amount, the demand priority adjustment coefficient, the economic status adjustment coefficient and the regional difference coefficient. The calculation result and the calculation basis are recommended to the reviewer for review. After the review is completed, the reviewer enters the subsidy review result into the system, feeds back the subsidy review result to the applicant, and publicizes the subsidy review result at the same time. The system also integrates a payment function. After the publicity period ends, the corresponding subsidy amount will be issued to the applicant for the application that has passed the review and has no objection.

[0016] Compared with the prior art, the advantages of the present invention are: (1) In the present invention, the demand assessment module uses user historical data to conduct objective, accurate and real-time analysis, avoid subjective bias, ensure the fairness and timeliness of the assessment results, comprehensively assess user needs from multiple angles, identify demand characteristics, provide a basis for service optimization and expansion, use a formulaic method to calculate the demand urgency coefficient, divide priorities by percentile, ensure the scientificity and rationality of the sorting, and effectively support resource allocation and service decision-making; (2) In the present invention, the economic status analysis module comprehensively collects the user's monthly income, daily expenditure and family asset information, generates a detailed report, and evaluates the economic health status by calculating the three key indicators of income-expenditure ratio, net asset ratio and debt ratio. The data of multiple months are obtained, and the average value of each indicator is calculated to ensure the stability and reliability of the evaluation results. The economic status assessment coefficient is calculated by a formula method and compared with the preset threshold to ensure the scientificity and rationality of the evaluation results. (3) In the present invention, the subsidy amount calculation module comprehensively considers the demand priority, economic status and regional differences, accurately calculates the subsidy amount, generates detailed results and basis, and automatically generates the basic subsidy amount, demand priority adjustment coefficient, economic status adjustment coefficient and regional difference coefficient, so as to ensure transparent calculation and facilitate audit. Different adjustment coefficients are set to treat different applicants fairly, simplify the audit process, reduce human intervention and improve audit efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a system block diagram of the present invention; Figure 2 This is a system block diagram of Embodiment 1 of the present invention; Figure 3 It is a logical flow diagram of the present invention. DETAILED DESCRIPTION

[0018] The following will combine the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all the embodiments. All other embodiments obtained by ordinary technicians in this field without creative work based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0019] Embodiment 1: Figure 1 and Figure 2 As shown, the present invention proposes a disability subsidy management and control system based on big data analysis, including a management and control platform, a user information collection module, a qualification review module, a demand assessment module, an economic status analysis module, and a subsidy amount calculation module; The management and control platform is connected to the qualification review module and the user information collection module in two-way communication. The management and control platform is connected to the demand assessment module, the subsidy amount calculation module and the economic situation analysis module in one-way communication. The demand assessment module is connected to the subsidy amount calculation module in one-way communication, and the economic situation analysis module is connected to the subsidy amount calculation module in one-way communication. User information collection module, used to provide application forms, support input of basic information and upload of relevant certification materials, and automatically connect to the database to obtain and integrate user history records; The user information collection module supports the following specific processes for filling in application forms, uploading supporting materials, and integrating user history records: When filling out the application form, users need to fill in basic information, including name, ID number, gender, age, disability type, payment account, contact information (mobile phone and email), residential address (province, city, district and detailed address), date of birth, family size and income source. Users are guided to provide valid information through input boxes and drop-down menus. For example, mobile phone numbers must be in 11-digit format, emails must comply with valid email formats, and address fields should be detailed to the house number. For family size, users need to fill in the total number of people (including themselves) and ensure that it is a positive integer; When uploading supporting documents, users need to upload supporting documents, including valid identity documents (such as scanned copies of ID cards or passports), income documents (such as payrolls for the last six months, pension notices, or self-employment-related documents), residence documents (such as a lease contract signed by both parties, water bills for the last six months or property certificates showing the user's name and address), and proof of medical or care needs (if the user has medical or care needs, a scanned copy of a health certificate or care-required document issued by a hospital or professional institution must be uploaded). All uploaded documents must be in PDF, JPEG, or PNG format, and the size limit for each file is 5MB. All uploaded supporting documents will be automatically formatted. When integrating user history records, the database is connected through a connection tool to automatically pull user history records, which include application history, subsidy collection record, social service record and credit record. The application history includes the user's past application status, application amount and application date. The subsidy collection record includes the type of subsidy and subsidy amount received by the user. The social service record includes the user's use of social services. The credit record includes the user's credit score and loan record. The pulled user history records are cleaned and standardized, and the cleaned and standardized user history records are integrated to form a comprehensive user history record archive. The user information collection module ensures the comprehensiveness and accuracy of information, simplifies the application process, and improves information processing efficiency by providing detailed basic information and supporting material upload functions; users are required to fill in information such as name, ID number, gender, age, disability type, payment account, contact information, residential address, date of birth, family size and source of income, and ensure the correct format through input boxes and drop-down menus. The uploaded supporting materials include proof of identity, proof of income, proof of residence and proof of medical or care needs, which must be in PDF, JPEG or PNG format, with a size limit of 5MB, and automatic format verification; the module connects to the database, automatically pulls application history, subsidy collection records, social service records and credit records, cleans and standardizes them, forms a comprehensive user history record archive, enhances data consistency and reliability, improves management efficiency and user experience, and ensures the security and confidentiality of information; in summary, the user information collection module provides efficient, secure and reliable information collection and management services to ensure data integrity and accuracy.

[0020] The qualification review module is used to check the completeness of application materials, confirm necessary information, automatically review user information according to standards, and confirm application qualifications; The specific process of the qualification review module checking application materials and reviewing user information is as follows: The system will check the completeness of the application materials through input verification (such as ensuring that all required fields are filled in and the format is in accordance with the requirements), file upload verification (ensuring that the file type and size meet the requirements), and database consistency check (verifying that the user's identity information is consistent with the system archive); The system will confirm the necessary information, including basic identity information (name, ID number, gender, age, disability category), contact information (mobile phone, email), financial status (income source, monthly income, asset status) and residential information (current address). The system will compare the information filled in by the user with the list of necessary information; The system will automatically review user information according to the set review standards, compare the user's information with the standards, and come up with the final review results. Users who meet all the standards will be marked as "eligible" and enter the subsequent process. Users who do not meet the standards will be marked as "ineligible" and will receive specific reasons and improvement suggestions provided by the system; The system will integrate all the review results, generate a detailed review report, and notify the applicant of the final review results, including whether the applicant meets the qualifications and the reasons; Demand assessment module, which is used to obtain historical data and statistical information, evaluate user needs, consumption habits and service usage records, and prioritize user needs according to urgency; The specific process of the demand assessment module evaluating user needs, consumption habits, and service usage records is as follows: Obtain and organize historical data and statistical information, including basic user information (such as name, ID number, gender, age, disability type, home address, contact information), consumption records (such as purchase date, product name, product category, consumption amount, payment method), service use records (such as applied subsidy project, application date, service provider, service content, number of services) and historical subsidy information (such as subsidy payment date, subsidy amount, approval result, evaluation result); By analyzing the consumption records and service usage records of users, it is possible to extract the demand characteristics of users, including the following demand characteristics: consumption frequency, consumption amount and service usage frequency. Consumption frequency refers to the number of times a user consumes per unit time, consumption amount refers to the total consumption amount of a user in a specific time period, and service usage frequency refers to the number of times a user applies for subsidies or services in a specific time period. The consumption habits and service usage records of users are evaluated through two indicators: income consumption ratio and service usage rate. The income consumption ratio refers to the ratio of a user's total consumption expenditure in a specific time period to his / her income in the same period. This indicator can reflect the user's economic status and can be used to evaluate whether the user needs additional subsidies. The service usage rate refers to the ratio of the number of services actually used by a user in a specific time period to the total number of optional services. This indicator reflects the user's utilization of existing services and can be used to evaluate whether service options need to be expanded. The qualification review module significantly improves efficiency and consistency through automated review, reduces manual intervention, speeds up the review process, ensures the fairness and consistency of each review, and avoids human bias; through input and file upload verification, it ensures the integrity of information and files, automatically checks format requirements, and ensures data consistency and readability; the system can immediately generate an audit report and notify the applicant of the results, provide specific reasons and improvement suggestions, and enhance user experience and transparency; database consistency checks ensure the security and confidentiality of user identity information, prevent information leakage, and comprehensively improve system reliability and user trust.

[0021] The specific process of the demand assessment module to prioritize user needs is as follows: Obtain the user's income consumption ratio and service utilization rate in multiple time periods, and sum and average them to obtain the average income consumption ratio PSX and average service utilization rate PFS. Obtain the demand urgency coefficient, where b1 and b2 are both preset proportional factor coefficients and b2>b1>0; By analyzing historical data, we can understand the impact of the income consumption ratio and service usage rate on the urgency of user demand. Based on the historical data, we can determine the specific values ​​of b1 and b2 to ensure that the calculated demand urgency coefficient can accurately reflect the actual urgency of users' needs. The calculated demand urgency coefficient XJ values ​​are sorted from small to large, and divided into different demand priorities according to percentiles. The top 20% XJ values ​​correspond to urgent demands, 20%-60% XJ values ​​correspond to high-priority demands, 60%-80% XJ values ​​correspond to medium-priority demands, and the bottom 20% XJ values ​​correspond to low-priority demands. The demand assessment module uses a data-driven approach to conduct objective, accurate and real-time analysis using historical data of users (such as consumption records, service usage records and economic conditions), avoiding subjective bias and ensuring the fairness and timeliness of the assessment results. The module comprehensively considers users' consumption habits, service usage records and economic conditions, and combines personalized data (such as consumption preferences, service usage frequency, etc.) to deeply understand user needs from multiple perspectives, identify demand characteristics and provide reference for service optimization and expansion. It adjusts weights and percentiles by preset proportional factors to prioritize needs, ensuring the scientific and reasonable sorting of needs and facilitating resource allocation and service decision-making. The module has the ability to continuously learn, constantly acquire and update user data, dynamically adjust assessment results, and optimize the assessment model based on actual application effects to improve the comprehensiveness and accuracy of the assessment. Finally, the assessment results are used for personalized service recommendations, significantly improving user experience and service satisfaction.

[0022] Embodiment 2: The technical solution of the embodiment of the present invention is different from that of embodiment 1 in that: like Figure 1 and Figure 3 As shown, the economic status analysis module is used to obtain the user's monthly income, daily expenses and family assets information, generate the user's income and expenditure report, and comprehensively evaluate the user's economic status; The specific process of the economic situation analysis module to generate income and expenditure reports and evaluate economic conditions is as follows: Obtain and organize the user's monthly income (including all sources of income such as wages, bonuses, subsidies, interest income, etc.), daily expenses (including expenses on daily necessities, housing, transportation, medical care, education, entertainment, etc.) and family asset information (including all assets such as real estate, vehicles, deposits, stocks, bonds, etc., but net assets after deducting liabilities (such as mortgages and car loans)), and generate an income and expenditure report. The income and expenditure report includes personal information (name, ID number, contact information, etc.), income section (details of monthly income sources, specific amounts of each income source, and total monthly income), expenditure section (details of daily expenditure categories, specific amounts of each expenditure category, and total monthly expenditure), and asset section (details of family asset categories, specific value of each asset, total asset value, total debt amount, and net asset value); The economic status of users is evaluated through three indicators: income-expenditure ratio, net asset ratio and debt ratio. The income-expenditure ratio refers to the ratio of all income earned by users in a specific period of time to the daily expenses incurred by users in a specific month. The higher the value of the income-expenditure ratio, the higher the income level of users and the better the economic status. The net asset ratio refers to the ratio of all assets owned by the user's family to all income earned by the user in a specific month. The higher the value of the net asset ratio, the more abundant the family assets and the better the economic status. The debt ratio refers to the ratio of all debts of the user's family to all assets owned by the user's family. The lower the value of the debt ratio, the lower the debt level and the better the economic status. Get the user's income-expenditure ratio, net asset ratio, and debt ratio in multiple months, and sum and average them to get the average income-expenditure ratio PSZ, average net asset ratio PJZ, and average debt ratio PFZ. The economic status assessment coefficient is obtained, where c1, c2, and c3 are all preset proportional factor coefficients, and c1, c2, and c3 are all greater than 0. The economic status assessment coefficient JZP is compared and analyzed with the preset economic status assessment coefficient threshold: By analyzing historical data, we can understand the impact of the income-expenditure ratio, net asset ratio and debt ratio on the user's economic status. Based on the historical data, we can determine the specific values ​​of c1, c2 and c3 to ensure that the calculated economic status assessment coefficient can accurately reflect the user's actual economic status. If the economic status assessment coefficient JZP is greater than the preset economic status assessment coefficient threshold, it indicates that the user's economic status is good; If the economic status assessment coefficient JZP is less than or equal to the preset economic status assessment coefficient threshold, it indicates that the user's economic status is poor; The economic status analysis module comprehensively collects information on users' monthly income, daily expenses and household assets, generates detailed reports, and evaluates economic health by calculating three key indicators: income-expenditure ratio, net asset ratio and debt ratio. Data for multiple months are obtained, and the average value of each indicator is calculated to ensure the stability and reliability of the evaluation results. The economic status assessment coefficient is calculated through a formulaic method and compared with the preset threshold to ensure the scientificity and rationality of the evaluation results.

[0023] The subsidy amount calculation module is used to calculate the subsidy amount based on demand priority, economic status assessment and regional differences, generate calculation results and basis, and recommend them to the reviewer for review; The specific process of calculating the subsidy amount by the subsidy amount calculation module is as follows: Obtain the user's demand priority and convert the demand priority into a demand priority adjustment coefficient. The specific values ​​of the demand priority adjustment coefficient are as follows: The demand priority adjustment factor corresponding to urgent demand is 1.2; The demand priority adjustment coefficient corresponding to the high priority demand is 1.0; The demand priority adjustment coefficient corresponding to the medium priority demand is 0.8; The demand priority adjustment coefficient corresponding to the low priority demand is 0.6; The converted need priority adjustment factor is multiplied by the basic subsidy amount to obtain the preliminary subsidy amount, which is set according to the disability category and relevant standards; Obtain the user's economic status assessment results and determine the economic status adjustment coefficient. The specific values ​​of the economic status adjustment coefficient are as follows: The economic adjustment coefficient corresponding to a user with good economic conditions is 0.7; The economic adjustment coefficient corresponding to the poor economic situation of users is 1.2; The second stage subsidy amount is obtained by multiplying the determined economic situation adjustment factor by the initial subsidy amount; The regional difference coefficient is determined according to the user's residential area. The specific values ​​of the regional difference coefficient are as follows: The regional variation coefficient corresponding to economically developed regions is 0.8; The regional variation coefficient corresponding to the economically average region is 1.0; The regional variation coefficient corresponding to the economically underdeveloped regions is 1.2; Multiply the determined regional difference coefficient by the second-stage subsidy amount to obtain the final subsidy amount; After the calculation is completed, the calculation result and calculation basis are automatically generated. The generated calculation result is the final subsidy amount. The calculation basis is the calculation parameters, which include the basic subsidy amount, demand priority adjustment coefficient, economic status adjustment coefficient and regional difference coefficient. The calculation result and calculation basis are recommended to the reviewer for review. After the review is completed, the reviewer will enter the subsidy review result into the system, feedback the subsidy review result to the applicant, and publicize the subsidy review result at the same time. The system also integrates the payment function. After the publicity period ends, the corresponding subsidy amount will be issued to the applicant for the application that has passed the review and has no objection; The subsidy amount calculation module achieves accurate calculation and fair distribution of subsidy amounts through multi-dimensional evaluation and dynamic adjustment, enhances the transparency and traceability of the system, and improves user experience and management efficiency. By comprehensively considering demand priorities, economic conditions and regional differences, the system ensures the rationality and fairness of subsidy amounts, achieves optimal allocation of resources, and improves user satisfaction and system reliability.

[0024] Working principle of the present invention: When in use, the present invention uses the user's historical data through the demand assessment module to conduct objective, accurate and real-time analysis, avoid subjective bias, ensure the fairness and timeliness of the assessment results, comprehensively assess user needs from multiple angles, identify demand characteristics, provide a basis for service optimization and expansion, use a formulaic method to calculate the demand urgency coefficient, divide priorities by percentile, ensure the scientificity and rationality of the sorting, effectively support resource allocation and service decision-making, and comprehensively collect the user's monthly income, daily expenses and family asset information through the economic situation analysis module to generate a detailed report, by calculating the three key indicators of income expenditure ratio, net asset ratio and debt ratio , evaluate economic health, obtain data from multiple months, calculate the average of each indicator, ensure the stability and reliability of the evaluation results, calculate the economic status assessment coefficient through a formulaic method, and compare it with the preset threshold to ensure the scientificity and rationality of the evaluation results, and use the subsidy amount calculation module to comprehensively consider the demand priority, economic status and regional differences, accurately calculate the subsidy amount, generate detailed results and basis, automatically generate the basic subsidy amount, demand priority adjustment coefficient, economic status adjustment coefficient and regional difference coefficient, ensure transparent calculation, facilitate review, set different adjustment coefficients, treat different applicants fairly, simplify the review process, reduce human intervention, and improve review efficiency.

[0025] The above are only preferred specific implementation modes of the present invention; however, the protection scope of the present invention is not limited thereto; any technician familiar with the technical field within the technical scope disclosed by the present invention; any equivalent replacement or change based on the technical solution and improved concept of the present invention shall be covered within the protection scope of the present invention.

Claims

1. A disability subsidy management and control system based on big data analysis, characterized in that: It includes a management and control platform, a user information collection module, a qualification review module, a demand assessment module, an economic situation analysis module, and a subsidy amount calculation module; User information collection module, used to provide application forms, support input of basic information and upload of relevant certification materials, and automatically connect to the database to obtain and integrate user history records; The qualification review module is used to check the completeness of application materials, confirm necessary information, automatically review user information according to standards, and confirm application qualifications; Demand assessment module, which is used to obtain historical data and statistical information, evaluate user needs, consumption habits and service usage records, and prioritize user needs according to urgency; The economic status analysis module is used to obtain the user's monthly income, daily expenses and family assets information, generate the user's income and expenditure report, and comprehensively evaluate the user's economic status; The subsidy amount calculation module is used to calculate the subsidy amount based on demand priority, economic status assessment and regional differences, generate calculation results and basis, and recommend them to reviewers for review.

2. According to claim 1, a disability subsidy management and control system based on big data analysis is characterized in that: The specific process of the user information collection module supporting application form filling, certification material uploading and user history record integration is as follows: When filling out the application form, users need to fill in basic information, including name, ID number, gender, age, disability type, payment account, contact information, residential address, date of birth, family size, and source of income. Users are guided to provide valid information through input boxes and drop-down menus; When uploading supporting documents, users need to upload supporting documents, including valid identity documents, income documents, residence documents, and medical or care needs documents. All uploaded documents must be in PDF, JPEG, or PNG format, and the size limit for each file is 5MB. All uploaded supporting documents will be automatically formatted. When integrating user historical records, the database is connected through a connection tool to automatically pull user historical records. User historical records include application history, subsidy collection record, social service record and credit record. Application history includes the user's past application status, application amount and application date. Subsidy collection record includes the type of subsidy and subsidy amount received by the user. Social service record includes the user's use of social services. Credit record includes the user's credit score and loan record. The pulled user historical records are cleaned and standardized, and the cleaned and standardized user historical records are integrated to form a comprehensive user historical record archive.

3. According to claim 2, a disability subsidy management and control system based on big data analysis is characterized in that: The specific process of the qualification review module checking application materials and reviewing user information is as follows: The system will check the completeness of the application materials through input verification, file upload verification and database consistency check; The system will confirm the necessary information, including basic identity information, contact information, financial status and residence information. The system will compare the information filled in by the user with the list of necessary information; The system will automatically review user information according to the set review standards, compare the user's information with the standards, and come up with the final review results. Users who meet all the standards will be marked as "eligible" and enter the subsequent process. Users who do not meet the standards will be marked as "ineligible" and will receive specific reasons and improvement suggestions provided by the system; The system will integrate all review results, generate a detailed review report, and notify the applicant of the final review results, including whether they meet the qualifications and the reasons.

4. According to the big data analysis-based disability subsidy management and control system of claim 1, it is characterized in that: The specific process of the demand assessment module assessing user needs, consumption habits and service usage records is as follows: Obtain and organize historical data and statistical information, including basic user information, consumption records, service usage records, and historical subsidy information; By analyzing the user's consumption records and service usage records, the user's demand characteristics can be extracted, including the following demand characteristics: consumption frequency, consumption amount and service usage frequency. The consumption frequency refers to the number of times the user consumes per unit time, the consumption amount refers to the total consumption amount of the user in a specific time period, and the service usage frequency refers to the number of times the user applies for subsidies or services in a specific time period. The user's consumption habits and service usage records are evaluated through two indicators: income consumption ratio and service utilization rate. The income consumption ratio refers to the ratio of the user's total consumption expenditure in a specific time period to his / her income in the same period. The service utilization rate refers to the ratio of the number of services actually used by the user in a specific time period to the total number of optional services.

5. According to claim 4, a disability subsidy management and control system based on big data analysis is characterized in that: The specific process of the demand assessment module to prioritize user needs is as follows: Obtain the user's income consumption ratio and service utilization rate in multiple time periods, and sum and average them to obtain the average income consumption ratio PSX and average service utilization rate PFS. Obtain the demand urgency coefficient, where b1 and b2 are both preset proportional factor coefficients and b2>b1>0; The calculated demand urgency coefficient XJ values ​​are sorted from small to large and divided into different demand priorities according to percentiles. The top 20% XJ values ​​correspond to urgent demands, 20%-60% XJ values ​​correspond to high-priority demands, 60%-80% XJ values ​​correspond to medium-priority demands, and the bottom 20% XJ values ​​correspond to low-priority demands.

6. A disability subsidy management and control system based on big data analysis according to claim 5, characterized in that: The specific process of the economic situation analysis module generating income and expenditure reports and evaluating economic conditions is as follows: Obtain and organize the user's monthly income, daily expenditure and family asset information, and generate an income and expenditure report, which includes personal information, income, expenditure and assets; The user's economic situation is assessed using three indicators: income-to-expenditure ratio, net asset ratio, and debt ratio. The income-to-expenditure ratio refers to the ratio of all income earned by the user in a specific period of time to the user's daily expenses incurred in a specific month. The net asset ratio refers to the ratio of all assets owned by the user's family to all income earned by the user in a specific month. The debt ratio refers to the ratio of all debts of the user's family to all assets owned by the user's family.

7. A disability subsidy management and control system based on big data analysis according to claim 6, characterized in that: Get the user's income-expenditure ratio, net asset ratio, and debt ratio in multiple months, and sum and average them to get the average income-expenditure ratio PSZ, average net asset ratio PJZ, and average debt ratio PFZ. The economic status assessment coefficient is obtained, where c1, c2, and c3 are all preset proportional factor coefficients, and c1, c2, and c3 are all greater than 0. The economic status assessment coefficient JZP is compared and analyzed with the preset economic status assessment coefficient threshold: If the economic status assessment coefficient JZP is greater than the preset economic status assessment coefficient threshold, it indicates that the user's economic status is good; If the economic status assessment coefficient JZP is less than or equal to the preset economic status assessment coefficient threshold, it indicates that the user's economic status is poor.

8. A disability subsidy management and control system based on big data analysis according to claim 7, characterized in that: The specific process of calculating the subsidy amount by the subsidy amount calculation module is as follows: Obtain the user's demand priority and convert the demand priority into a demand priority adjustment coefficient. The specific values ​​of the demand priority adjustment coefficient are as follows: The demand priority adjustment factor corresponding to urgent demand is 1.2; The demand priority adjustment coefficient corresponding to the high priority demand is 1.0; The demand priority adjustment coefficient corresponding to the medium priority demand is 0.8; The demand priority adjustment coefficient corresponding to the low priority demand is 0.6; The initial subsidy amount is obtained by multiplying the converted need priority adjustment coefficient by the basic subsidy amount. The basic subsidy amount is set according to the disability category and relevant standards.

9. A disability subsidy management and control system based on big data analysis according to claim 8, characterized in that: Obtain the user's economic status assessment results and determine the economic status adjustment coefficient. The specific values ​​of the economic status adjustment coefficient are as follows: The economic adjustment coefficient corresponding to a user with good economic conditions is 0.7; The economic adjustment coefficient corresponding to the poor economic situation of users is 1.2; The second stage subsidy amount is obtained by multiplying the determined economic situation adjustment factor by the initial subsidy amount; The regional difference coefficient is determined according to the user's residential area. The specific values ​​of the regional difference coefficient are as follows: The regional variation coefficient corresponding to economically developed regions is 0.8; The regional variation coefficient corresponding to the economically average region is 1.0; The regional variation coefficient corresponding to the economically underdeveloped regions is 1.2; Multiply the determined regional difference coefficient by the second-stage subsidy amount to obtain the final subsidy amount.

10. A disability subsidy management and control system based on big data analysis according to claim 9, characterized in that: After the calculation is completed, the calculation result and calculation basis are automatically generated. The generated calculation result is the final subsidy amount, and the calculation basis is the calculation parameters, which include the basic subsidy amount, demand priority adjustment coefficient, economic status adjustment coefficient and regional difference coefficient. The calculation result and calculation basis are recommended to the reviewer for review. After the review, the reviewer enters the subsidy review result into the system, and feeds back the subsidy review result to the applicant. At the same time, the subsidy review result is announced. The system also integrates payment function. After the announcement period ends, for applications that have passed the review and have no objections, the corresponding subsidy amount will be issued to the applicant.

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