A Hybrid Intelligent Classification Model Based on Multilayer Perceptron Neural Networks and Fuzzy Regression for Credit Scoring Problems
Author(s) -
M. Khashei,
Sh. Torbat
Publication year - 2019
Publication title -
journal of computational methods in engineering
Language(s) - English
Resource type - Journals
eISSN - 2423-5741
pISSN - 2228-7698
DOI - 10.29252/jcme.37.2.97
Subject(s) - computer science , artificial intelligence , artificial neural network , multilayer perceptron , machine learning , fuzzy logic , neuro fuzzy , data mining , perceptron , regression , regression analysis , fuzzy control system , mathematics , statistics
Financial crises in banking systems are due to inability to manage credit risks. Credit scoring is one of the risk management techniques that analyze the borrower's risk. In this paper, using the advantages of computational intelligence as well as soft computing methods, a new hybrid approach is proposed in order to improve credit risk management. In the proposed method, for modeling in uncertainty conditions, parameters of the neural network, including weights and errors, are considered * بتاکم لوئسم : :یکینورتکلا تسپ ،تا s.torbat@in.iut.ac.ir D ow nl oa de d fr om iu tjo ur na ls .iu t.a c. ir at 1 5: 02 IR S T o n T hu rs da y N ov em be r 19 th 2 02 0 [ D O I: 10 .2 92 52 /jc m e. 37 .2 .9 7 ]
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