Abstract
This study integrates the characteristics of credit risk rating and artificial intelligence technology into a credit risk rating model based on fuzzy neural network. The combination of fuzzy theory and neural network provides a good foundation for credit risk rating, making this model with fewer parameters, faster learning and less training samples. This study confirms that fuzzy neural network is an effective method for credit risk rating. The results of this study can solve the shortcomings in existing credit risk rating model and provide more information for decision-making reference.
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Zhu, KJ., Chen, PC., Chang, YT. (2010). A Credit Risk Rating Model Based on Fuzzy Neural Network. In: Zeng, Z., Wang, J. (eds) Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12990-2_19
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DOI: https://doi.org/10.1007/978-3-642-12990-2_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12989-6
Online ISBN: 978-3-642-12990-2
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