Model and application of farmers' credit risk early warning system based on T-S fuzzy neural network application.

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  • Author(s): Wang H;Wang H
  • Source:
    Mathematical biosciences and engineering : MBE [Math Biosci Eng] 2022 May 27; Vol. 19 (8), pp. 7886-7898.
  • Publication Type:
    Journal Article; Research Support, Non-U.S. Gov't
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: American Institute of Mathematical Sciences;; _b Beihang University Country of Publication: United States NLM ID: 101197794 Publication Model: Print Cited Medium: Internet ISSN: 1551-0018 (Electronic) Linking ISSN: 15471063 NLM ISO Abbreviation: Math Biosci Eng Subsets: MEDLINE
    • Publication Information:
      Original Publication: Springfield, MO, USA : [S.l.] : American Institute of Mathematical Sciences; Beihang University
    • Subject Terms:
      Agriculture* ; Farmers*; China ; Humans ; Neural Networks, Computer
    • Abstract:
      In China, farmers' loan difficulties have become a major problem restricting increases in farmers' incomes and the economic development of rural areas. The existing studies of the management and control of farmers' credit risk have mostly been pre-management, which cannot efficiently prevent and reduce the occurrence of farmers' credit risk in time. This paper uses the T-S neural network model to build a farmers' credit risk early warning system so that formal financial institutions can predict the occurrence of and changes in the farmers' credit risks in a timely manner and quickly undertake countermeasures to reduce losses. After training and testing, a model with a higher degree of fit is used to analyze the credit level of farmers in Shaanxi Province from 2016 to 2018. The results demonstrate that the credit level of farmers in this area is continuously improving, in agreement with the actual situation. The results also show that the prediction accuracy of the T-S fuzzy neural network is high, verifying the rationality of the selection of test samples.
    • Contributed Indexing:
      Keywords: T-S fuzzy neural network; early warning system; farmers' credit risk
    • Publication Date:
      Date Created: 20220708 Date Completed: 20220711 Latest Revision: 20220809
    • Publication Date:
      20221213
    • Accession Number:
      10.3934/mbe.2022368
    • Accession Number:
      35801448