Alternative diagnosis of corporate bankruptcy: A neuro fuzzy approach |
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| Authors: | Hsueh-Ju Chen Shaio Yan Huang Chin-Shien Lin |
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| Affiliation: | 1. CISUC - Department of Informatics Engineering, University of Coimbra, Pólo 2, Coimbra 3030–290, Portugal;2. College of Computer Science and Technology (Software College), Henan Polytechnic University, 2001 Century Avenue, Jiaozuo, 454003 Henan, PR China;3. Department of Mathematics, University of Coimbra, Praa Dom Dinis, Coimbra 3001–501, Portugal;1. Université de Lille, IAE Lille, Laboratoire Rime Lab. EA7396, 104 Avenue de Peuple Belge, 59000, Lille, France;2. Université de Paris Nanterre, IUT de Ville d''Avray, 200 Avenue de la République, 92001, Nanterre, France;1. School of Information and Engineering, Huanghe Science and Technology College, Zhengzhou, Henan 450063, PR China;2. Math department of Southeast university, Nanjing, Jiangsu 210000, PR China |
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| Abstract: | Bankruptcy filings are as high today as ever, calling into question the efficacy of existing bankruptcy prediction models. This paper tries to provide an alternative for bankruptcy prediction by using neuro fuzzy, a hybrid approach combining the functionality of fuzzy logic and the learning ability of neural networks. The empirical results show that neuro fuzzy demonstrates a better accuracy rate, lower misclassification cost and higher detecting power than does logit regression, meaning neuro fuzzy could be a great help in providing warnings of impending bankruptcy. Also, its comprehensive explanation about mapping functions among variables presumably provides a foundation for further development of theory and testing of the membership function shape, the transfer function, the methods to aggregate, the methods to defuzzify, and so on. |
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| Keywords: | Bankruptcy Neural network Fuzzy logic Neuro fuzzy |
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