A new RBF neural network and its application on individual credit rating in banks

doi:10.7523/j.issn.1002-1175.2013.03.003

Abstract

Abstract:

We mainly focus on the application of RBF neural networks in individual credit evaluation. Considering that the traditional RBF neural networks can only deal with the numerical value and that it is sensitive to the noisy data and the initial clustering centers, we propose a new RBF neural network combined with fuzzy K-Prototypes algorithm, which can deal with mixed data and is less sensitive to the noisy data and the initial clustering centers. The experimental results on the credit data show that the new RBF neural network has higher accuracy and robustness than the traditional one.

Key words: RBF neural networks, fuzzy K-Prototypes algorithm, categorical data, credit rating

CLC Number:

F830.51

LAN Run-Rong, CHENG Xi-Jun. A new RBF neural network and its application on individual credit rating in banks[J]. , 2013, 30(3): 298-303.

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