نویسندگان

دانشکده مهندسی صنایع و برنامه‌ریزی سیستم‌ها، دانشگاه صنعتی اصفهان، اصفهان

چکیده

بحران‌های مالی موجود در نظام‌های بانکی ناشی از عدم توانایی در مدیریت ریسک‌های اعتباری است. امتیازدهی اعتباری یکی از تکنیک‌های مدیریت ریسک است که ریسک وام‌گیرنده را تحلیل می‌کند. در این مقاله با استفاده از مزایای روش‌های هوش محاسباتی و محاسبات نرم یک روش ترکیبی جدید به‌منظور بهبود مدیریت ریسک‌های اعتباری ارائه شده ‌‌است. در روش پیشنهادی، به‌منظور مدل‌سازی در شرایط عدم‌ قطعیت، پارامترهای شبکه عصبی، شامل وزن‌ها و خطاها، به‌صورت فازی در‌نظر گرفته شده‌اند. در این روش، ابتدا سیستم مورد مطالعه با استفاده از شبکه‌های عصبی متامدل‌بندی ‌شده و سپس با به‌کارگیری استنتاجات فازی تصمیم بهینه با بیشترین میزان برتری تعیین خواهد ‌شد. نتایج حاصل از به‌کارگیری روش پیشنهادی بیانگر کارامدی و دقت بالای این روش در تحلیل مسائل امتیازدهی اعتباری است.

کلیدواژه‌ها

عنوان مقاله [English]

A Hybrid Intelligent Classification Model Based on Multilayer Perceptron Neural Networks and Fuzzy Regression for Credit Scoring Problems

نویسندگان [English]

  • M. Khashei
  • Sh. Torbat

چکیده [English]

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 in the form of fuzzy numbers. In this method, the underlying system is firstly modeled using neural networks and then, using fuzzy inferences, the optimal decision will be determined with the highest degree of superiority. Empirical results of using the proposed method indicate the efficiency and high accuracy of this method in analyzing credit rating problems.

کلیدواژه‌ها [English]

  • Credit scoring
  • Classification methods
  • Multilayer perceptrons (MLPs)
  • artificial neural networks
  • fuzzy logic
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