An Adaptive Fuzzy Neural Network Model for Bankruptcy Prediction of Listed Companies on the Tehran Stock Exchange
محل انتشار: ماهنامه بین المللی مهندسی، دوره: 30، شماره: 12
سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 454
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شناسه ملی سند علمی:
JR_IJE-30-12_009
تاریخ نمایه سازی: 1 اردیبهشت 1397
چکیده مقاله:
Nowadays, prediction of corporate bankruptcy is one of the most important issues which have received great attentions among academia and practitioners. Although several studies have been accomplished in the field of bankruptcy prediction, less attention has been devoted for proposing a systematic approach based on fuzzy neural networks. The present study proposes fuzzy neural networks to predict bankruptcy of the listed companies in the Tehran stock exchange. Four input variables including growth, profitability, productivity and asset quality were used for prediction purpose. Moreover, the Altman s Z score is used as the output variable. The results reveal that the proposed fuzzy neural network model has a high performance for the bankruptcy prediction of the companies
کلیدواژه ها:
نویسندگان
A.H Azadnia
Department of Industrial Engineering, Ayatollah Amoli Branch, Islamic Azad University,Amol, Iran
A Siahi
Department of Management, Firuzkuh Branch, Islamic Azad University, Firuzkuh, Iran
M Motameni
Department of Mathematics, Qaemshahr Branch, Islamic Azad University,Qaemshahr, Iran