Forecast Research About Chongqing Basic Pension Fund Revenue And Expenditure Based On Grey BP Neural Network

The basic pension insurance provides a source of income to the majority of retireesfor protecting their basic living needs. The balance of payment problems of the pensioninsurance fund is directly related to the cause of sustainable development of China'sold-age insurance, the study has important practical significance.This article is in order to study Chongqing urban enterprise employees' basicpension insurance fund balance：First of all, generalized the correlation theory of the basic pension insurance,including the financing models,the way of total fat and the composition of income andexpenditure;Secondly, briefly introduced the grey GM (1,1) model and its improved method,and the use of BP neural network to GM (1,1) model for residual correction method;Thirdly, focus on the analysis of Chongqing basic pension insurance fund'spayments situation,on the basis of analyzing the relevant factors which affect thepension Fund, constructed mathematical model of the basic pension insurance fundrevenues and expenditures under the new system.Then, Based on the2005-2010years'relevant data of Chongqing basic pension insurance for urban enterprise workers, usedGray GM(1,1) prediction model combined with BP neural network theory to forecastthe relevant factors during target period(2011-2020years).Finally, according to the predictive value and revenue model to calculate the basicpension fund income and expenses value during target period, then draw a conclusion:In2019before, the pension fund balance is greater than zero, but then there will beaccumulated fund gap. Therefore, from the aspect of the coverage, the contributionrate, collection rate, replacement rate, retirement age and other parameters, proposedmeasures and suggestions to improve the basic pension insurance fund balance ofpayments problems.