Research On Forecasting Farmers' Ability To Acquire Loans Based On Cloud Model

Rural financial capital was the driving force for the development of rural households.The general lack of qualified household collateral led to a certain degree of financial repression.How to effectively distinguish the ability of farmers to obtain loans,reduce the risk of default,and formulate more targeted financial poverty alleviation policies.The study of “Accurate poverty”and “Rural revitalization”required the support of rural finance.Self-acquisition ability was an important indicator for the healthy development of farmers,and it was of great significance to solve the problem of financial rationing.From the perspective of farmers' ability to obtain loans,this paper used the actual survey data and Logit Regression Model to analyze the factors affecting farmers' ability to obtain loans,established a predictive index system for farmers' ability to obtain loans,built a model of subjective and objective weights,and used the actual data of farmers to verify and comparative analysis.Aiming to make a reasonable assessment of farmers' ability to obtain loans and provide relevant recommendations for the sustainable development of rural lending.The main contents are as follows: this paper took farmers as the research object and defined the concept of farmer loans through the combing of the literature on farmers' borrowing.According to the field research data,the regression analysis was carried out to screen out the factors that have significant influence on the farmers' ability to obtain loans.From the four aspects of household characteristics,production characteristics,material capital characteristics and social capital,the evaluation index system of farmers' ability to obtain loans was established.On the basis of the constructed index system,in order to overcome the shortcomings of the single weighting method,this paper used the subjective and objective combined weighting method based on the order-coefficient coefficient to determine the weight of the index.Finally,this paper introduced the cloud model into the prediction of the availability of farmer loans,built a model based on cloud model for farmers to obtain loan capacity,and selected 30 farmers' real data for instance verification.Through the analysis of the forecast results,farmers' loan demand is strong,the satisfaction rate is low,and the collateral and solvency are still in an important evaluation position.In the production characteristics of farmers,the type of family business and participation in cooperatives can make farmers obtain more information.In social relations,the input of maintaining relationship is positively related to the stability of relationship.The degrees of intimacy and trust have positive effects on farmers' loans.Relatives There may not be a destabilizing effect between monetary interests,and mutual trust occupies a major position.The comparison between OLS regression method and BP neural network method verifies that the method studied in this paper has certain practicability and accuracy.(1)For farmers,they must strengthen their own subjective initiative,improve their cultural skills,and actively participate in cooperative organizations.(2)For financial institutions,first,improve the propaganda of financial institutions and improve the propaganda methods;second,financial institutions should increase interaction with organizations such as rural governments or cooperatives to encourage farmers to jointly protect and group;third,financial institutions The “Internet Plus” model of financial products and services should be explored.(3)For the government level,accelerate the construction of a new type of professional peasant team,increase guidance and support for farmers' professional cooperatives,set up a special farmer development fund,and establish a unified management platform for farmers' information.Effectively increase farmers' income and improve the rural financial service system.