Design and Implementation of a Rural Social Security System Based on Deep Learning

Yan Zhao,Wenqing Wu

doi:10.1155/2021/8676301

Abstract

After the reform and opening up, my country’s economic level and total national strength have achieved unprecedented growth. The building of a well-off society in an all-round way is moving towards a harmonious society. The development of social security is also an important part of the development and improvement of a socialist harmonious society. This article is aimed at designing a rural social security system based on deep learning algorithms, using sample collection and statistical analysis methods, collecting samples, simplifying the algorithm, and establishing a new rural social security system. The data collected by the system shows that the proportion of farmers who choose very satisfied, satisfied, average, dissatisfied, and very dissatisfied with the satisfaction of the new rural insurance is 8.94%, 45.53%, 34.96%, 8.13%, and 2.44%. It can be seen that the proportion of farmers who choose to be satisfied is the largest, and more than 10.0% of farmers choose to be dissatisfied or very dissatisfied. Investigate the factors that farmers worry about participating in the new rural insurance, and the questionnaire options can also be set to multiple choices. The survey results show that 29.27% of the farmers think that the individual payment for participating in the new rural insurance is higher; 26.02% of the farmers believe that they do not understand the new rural insurance system; 9.76% of the farmers believe that it is unnecessary to pay for the new rural insurance; 22.76% of farmers choose to rely on themselves or their children in the future; 27.64% of farmers think that the system is unstable. It has basically realized the design of a brand new rural social security system starting from the deep learning of semantic computing.

Highlights

IntroductionThe rural social security system (the new rural endowment insurance system is a personal endowment insurance account in which the state establishes a lifetime record for each new rural insurance participant; individual payment, collective subsidies, and other economic organizations, social welfare organizations, and individual subsidies for the insured person’s payment, and the local government’s subsidy for the insured person’s payment, all are credited to the personal account) is an indispensable system of people’s livelihood security proposed based on our country’s social status quo
The rural social security system is an indispensable system of people’s livelihood security proposed based on our country’s social status quo
Investigate the factors that farmers worry about participating in the new rural insurance, and the questionnaire options can be set to multiple choices

Summary

Introduction

The rural social security system (the new rural endowment insurance system is a personal endowment insurance account in which the state establishes a lifetime record for each new rural insurance participant; individual payment, collective subsidies, and other economic organizations, social welfare organizations, and individual subsidies for the insured person’s payment, and the local government’s subsidy for the insured person’s payment, all are credited to the personal account) is an indispensable system of people’s livelihood security proposed based on our country’s social status quo. Most countries and regions are facing the problem of aging population. The issue of aging has increasingly become a hot issue of concern to various countries. At this stage, my country has become one of the countries with the largest aging population. Through comparison between the urban and rural areas, the problem of rural population aging is even more serious. With the continuous development of the national economy, the outflow of agricultural laborers and the development of family planning have resulted in the labor force being less than the elderly population. These undoubtedly increase the burden of agricultural pensions.

Objectives

Methods

Results

Conclusion