Rural public service optimization decision support system based on big data analysis

Abstract

The invention relates to the technical field of big data, in particular to a rural public service optimization decision support system based on big data analysis, which comprises a data acquisition module, a data storage and management module, a data analysis and mining module, a data modeling module, a decision support module and a user interaction and feedback module. And the data acquisition module is used for acquiring related data of rural public services from different channels, establishing interfaces with government affair information systems of all departments of the government, and automatically transmitting and acquiring the data. Scientific decision-making basis, real-time data analysis and decision making are provided for the government and related management departments, decisions are made accurately and timely, it is ensured that resources can be efficiently and reasonably distributed to most needed places, resource waste is reduced, and overall development of rural areas is promoted.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a rural public service optimization decision support system based on big data analysis. Background Art

[0002] With the rapid development of society, agriculture, as a core industry, plays a vital role in promoting technology and infrastructure construction in enhancing the overall vitality of the rural economy and ensuring the quality of life of farmers. The demand for public services in rural areas is increasing. However, the traditional allocation of public service resources usually lacks scientific data support, resulting in inefficient resource allocation, imbalance, unfair distribution, and untimely response. The rural public service sector is facing problems such as unbalanced resource allocation and low service efficiency, especially in remote areas with poor transportation conditions and low level of informatization.

[0003] The existing management systems often rely on manual decision-making and lack intelligence and real-time data tracking and evaluation mechanisms, and are unable to effectively respond to the diversified public service needs in rural areas. Therefore, a rural public service optimization decision support system based on big data analysis is proposed. Summary of the invention

[0004] In view of this, the present invention provides a rural public service optimization decision support system based on big data analysis to solve or alleviate the technical problems existing in the prior art and at least provide a beneficial option.

[0005] The technical solution of the present invention is implemented as follows: a rural public service optimization decision support system based on big data analysis includes a data acquisition module, a data storage and management module, a data analysis and mining module, a data modeling module, a decision support module and a user interaction and feedback module;

[0006] The data collection module is used to collect relevant data on rural public services from different channels, establish interfaces with the government information systems of various government departments, automatically transmit and collect data, and then clean, integrate and convert the collected raw data to remove invalid, duplicate or erroneous data;

[0007] The data storage and management module is used to store and collect government department data, IoT device data, Internet platform data and pre-processed data, regularly check and verify the stored data, regularly back up the data, and record data version information;

[0008] The data analysis and mining module is used to perform basic statistical calculations on rural public service-related data, conduct horizontal comparisons of rural public service conditions in different regions, explore the correlation between various elements of rural public services and between public services and other related factors, and infer the causal relationship between rural public service-related variables;

[0009] The data modeling module is used to select characteristic variables closely related to the modeling target from the massive amount of rural public service data that has been collected, stored and preprocessed, and to model the classification problems related to rural public services;

[0010] The decision support module generates decision plans based on the provided data, analysis results and model operation results;

[0011] The user interaction and feedback module presents data query, analysis result viewing, and decision plan browsing through the interface, and establishes multiple feedback channels so that various users can convey optimization suggestions to the system management party.

[0012] Further preferred is the data collection module, where data sources include government department data, IoT device data, Internet platform data and field survey data. By connecting with government department system data, government department data is collected, and Internet public data is captured using web crawler technology. The mobile terminal conducts survey entry through the mobile government affairs platform, and the cleaned and converted data from different data sources are integrated according to unified rules to build a complete rural public service related data set.

[0013] Further preferably, the data storage and management module uses a relational database to store data with a clear structure that needs to strictly comply with transaction consistency requirements, and integrates massive data from multiple data sources through a data warehouse for unified organization and management.

[0014] Further preferably, in the data storage and management module, when managing data, the security, quality and version of the data are managed, different levels of permissions are set for different users of the system, the stored data is encrypted, and the data is backed up regularly. When managing data quality, a data management monitoring mechanism is established, the data is checked and verified regularly, reasonable update cycles are set for different types of data, and each update and modification operation of the data is recorded.

[0015] Further preferred, the data analysis and mining module analyzes the data descriptiveness, correlation, clustering and predictiveness, performs basic statistical calculations on rural public service related data, analyzes the distribution pattern of rural public service related data, makes a horizontal comparison of the public service conditions in rural areas of different regions, finds out the differences in the level of development of public services, uses correlation analysis statistical methods to explore the correlation between the various elements of rural public services and between public services and other related factors, and uses time series analysis and machine learning algorithms to predict the future demand scale and demand structure of rural public services based on past demand data for rural public services and influencing factors related to demand.

[0016] Further preferably, the data modeling module selects characteristic variables closely related to the modeling objectives from the massive rural public service data that have been collected, stored and preprocessed, and reasonably divides the data set into training set, validation set and test set for adjusting the hyperparameters of the model.

[0017] Further optimized, the decision support module, combined with the rural development plan and the actual situation, clarifies the specific decision-making goals according to the multi-dimensional evaluation indicators, conducts a comprehensive analysis of the internal and external risks faced during the implementation of the decision-making plan, and sets corresponding early warning indicators and reasonable thresholds for the various risks identified.

[0018] Further preferably, the user interaction and feedback module performs interactive operations on the visually displayed data, establishes multiple feedback channels, and classifies and organizes the collected feedback information.

[0019] The embodiment of the present invention has the following advantages due to the adoption of the above technical solution:

[0020] The present invention provides a scientific decision-making basis for the government and relevant management departments by deeply analyzing various data such as public service needs, resource distribution, utilization efficiency and public satisfaction in rural areas. It also enables real-time data analysis and decision-making, and makes accurate and timely decisions to ensure that resources can be efficiently and reasonably allocated to where they are most needed, thereby reducing resource waste and promoting the overall development of rural areas.

[0021] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0024] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0025] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0026] like Figure 1 As shown, an embodiment of the present invention provides a rural public service optimization decision support system based on big data analysis, including a data acquisition module, a data storage and management module, a data analysis and mining module, a data modeling module, a decision support module and a user interaction and feedback module;

[0027] The data collection module is used to collect relevant data on rural public services from different channels, establish interfaces with the government information systems of various government departments, automatically transmit and collect data, and then clean, integrate and convert the collected raw data to remove invalid, duplicate or erroneous data;

[0028] The data storage and management module is used to store and collect government department data, IoT device data, Internet platform data and pre-processed data, regularly check and verify the stored data, regularly back up the data, and record data version information;

[0029] The data analysis and mining module is used to perform basic statistical calculations on rural public service-related data, conduct horizontal comparisons of rural public service conditions in different regions, explore the correlation between various elements of rural public services and between public services and other related factors, and infer the causal relationship between rural public service-related variables;

[0030] The data modeling module is used to select characteristic variables closely related to the modeling target from the massive amount of rural public service data that has been collected, stored and preprocessed, and to model the classification problems related to rural public services;

[0031] The decision support module generates decision plans based on the provided data, analysis results and model operation results;

[0032] The user interaction and feedback module presents data query, analysis result viewing, and decision plan browsing through the interface, and establishes multiple feedback channels so that various users can convey optimization suggestions to the system management party.

[0033] In one embodiment, the data collection module, whose data sources include government department data, IoT device data, Internet platform data and field survey data, collects government department data by connecting with government department system data, and uses web crawler technology to capture Internet public data. The mobile terminal conducts survey and input through the mobile government affairs platform, and integrates the cleaned and converted data from different data sources according to unified rules to build a complete rural public service related data set; collects farmers' information when they use it.

[0034] In one embodiment, the data storage and management module uses a relational database to store data with a clear structure that needs to strictly comply with transaction consistency requirements, and integrates massive data from multiple data sources through a data warehouse for unified organization and management; the data analysis module is used to perform correlation analysis to accurately determine the acceptance and actual needs of different farmer groups for agricultural technology.

[0035] In one embodiment, in the data storage and management module, when managing data, the security, quality and version of the data are managed, different levels of permissions are set for different users of the system, the stored data is encrypted, and the data is backed up regularly. When managing data quality, a data management monitoring mechanism is established, the data is checked and verified regularly, a reasonable update cycle is set for different types of data, and each update and modification operation of the data is recorded.

[0036] In one embodiment, the data analysis and mining module analyzes the descriptiveness, correlation, clustering and predictiveness of the data, performs basic statistical calculations on the data related to rural public services, analyzes the distribution patterns of the data related to rural public services, compares the public services in rural areas of different regions horizontally, finds out the differences in the development levels of public services, uses correlation analysis statistical methods to mine the correlations between the various elements of rural public services and between public services and other related factors, and uses time series analysis and machine learning algorithms to predict the scale and structure of future rural public service demand based on past demand data for rural public services and influencing factors related to demand. It collects and analyzes the existing agricultural infrastructure data in rural areas when farmers use it, so as to optimize and improve the promotion plans, technical training content, follow-up services, etc., and continuously improve the quality of agricultural technology promotion.

[0037] In one embodiment, the data modeling module selects characteristic variables that are closely related to the modeling objectives from the massive rural public service data that have been collected, stored and preprocessed, and reasonably divides the data set into a training set, a validation set and a test set for adjusting the hyperparameters of the model; the prediction model constructed based on the data modeling module, when used by farmers, comprehensively considers the intensity of policy support, the market demand trend for agricultural products, and the promotion cycle of agricultural technology itself, and generates appropriate agricultural technology promotion plans for different regions and different farmer groups.

[0038] In one embodiment, the decision support module, in combination with the rural development plan and the actual situation faced, clarifies the specific decision goals and sets them according to multi-dimensional evaluation indicators, conducts a comprehensive analysis of the internal and external risks faced during the implementation of the decision plan, and sets corresponding early warning indicators and reasonable thresholds for the various risks identified.

[0039] In one embodiment, the user interaction and feedback module performs interactive operations on the visually displayed data, establishes multiple feedback channels, and classifies and organizes the collected feedback information.

[0040] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of various changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A rural public service optimization decision support system based on big data analysis, characterized by: It includes data acquisition module, data storage and management module, data analysis and mining module, data modeling module, decision support module and user interaction and feedback module; The data collection module is used to collect relevant data of rural public services from different channels, establish interfaces with the government information systems of various government departments, automatically transmit and collect data, and then clean, integrate and convert the collected raw data to remove invalid, duplicate or erroneous data; The data storage and management module is used to store and collect government department data, IoT device data, Internet platform data and pre-processed data, regularly check and verify the stored data, regularly back up the data, and record data version information; The data analysis and mining module is used to perform basic statistical calculations on rural public service related data, to compare the public service conditions of rural areas in different regions, to explore the correlation between various elements of rural public services and between public services and other related factors, and to infer the causal relationship between rural public service related variables; The data modeling module is used to select characteristic variables closely related to the modeling target from the massive amount of rural public service data that has been collected, stored and preprocessed, and to model the classification problems related to rural public services; The decision support module generates a decision plan based on the provided data, analysis results and model operation results; The user interaction and feedback module presents data query, analysis result viewing, and decision plan browsing through an interface, and establishes multiple feedback channels, so that various users can convey optimization suggestions to the system management party.

2. The rural public service optimization decision support system based on big data analysis according to claim 1 is characterized by: The data collection module, whose data sources include government department data, IoT device data, Internet platform data and field survey data, collects government department data by connecting with government department system data, and uses web crawler technology to capture Internet public data. The mobile terminal conducts survey and input through the mobile government affairs platform, and integrates the cleaned and converted data from different data sources according to unified rules to build a complete rural public service related data set.

3. The rural public service optimization decision support system based on big data analysis according to claim 1 is characterized by: The data storage and management module uses a relational database to store data with a clear structure that needs to strictly comply with transaction consistency requirements, and integrates massive data from multiple data sources through a data warehouse for unified organization and management.

4. The rural public service optimization decision support system based on big data analysis according to claim 1 is characterized by: In the data storage and management module, when managing data, the security, quality and version of the data are managed, different levels of permissions are set for different users of the system, the stored data is encrypted, and the data is backed up regularly. When managing data quality, a data management monitoring mechanism is established, the data is checked and verified regularly, a reasonable update cycle is set for different types of data, and each update and modification operation of the data is recorded.

5. The rural public service optimization decision support system based on big data analysis according to claim 1 is characterized by: The data analysis and mining module analyzes the descriptiveness, correlation, clustering and predictiveness of the data, performs basic statistical calculations on the data related to rural public services, analyzes the distribution patterns of the data related to rural public services, compares the public service conditions in rural areas of different regions horizontally, finds out the differences in the levels of development of public services, uses correlation analysis statistical methods to mine the correlations between the various elements of rural public services and between public services and other related factors, and uses time series analysis and machine learning algorithms to predict the future demand scale and demand structure of rural public services based on past demand data for rural public services and influencing factors related to demand.

6. The rural public service optimization decision support system based on big data analysis according to claim 1 is characterized by: The data modeling module selects characteristic variables closely related to the modeling objectives from the massive rural public service data that have been collected, stored and preprocessed, and reasonably divides the data set into a training set, a validation set and a test set for adjusting the hyperparameters of the model.

7. The rural public service optimization decision support system based on big data analysis according to claim 1 is characterized by: The decision support module combines rural development plans and actual situations, clarifies specific decision goals and sets them according to multi-dimensional evaluation indicators, conducts a comprehensive analysis of internal and external risks faced during the implementation of decision plans, and sets corresponding early warning indicators and reasonable thresholds for various risks identified.

8. The rural public service optimization decision support system based on big data analysis according to claim 1 is characterized by: The user interaction and feedback module performs interactive operations on the visually displayed data, establishes multiple feedback channels, and classifies and organizes the collected feedback information.

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