Journal of University of Chinese Academy of Sciences >
A new RBF neural network and its application on individual credit rating in banks
Received date: 2012-04-25
Revised date: 2012-10-11
Online published: 2012-10-11
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.
LAN Run-Rong , CHENG Xi-Jun . A new RBF neural network and its application on individual credit rating in banks[J]. Journal of University of Chinese Academy of Sciences, 2013 , 30(3) : 298 -303 . DOI: 10.7523/j.issn.1002-1175.2013.03.003
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