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Notice of Retraction
An Application of the Combination of Principal Component Analysis and BP Neural Network to Credit Assessment in the Commercial Banks

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2 Author(s)
Li Bo ; Sch. of Econ. & Manage., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China ; Xu Congwei

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

The credit risk assessment is the most difficulty in the credit risk management in commercial banks, so the combination method of principal component analysis and BP neural network based on biology nerve cell was introduced in detail according to the idea of combination forecasting. The principle component analysis is used to handle on input variables in advance to solve the problem of the inefficiency in BP neural network owing to the excessive input variables. Then the combination method is applied to credit risk assessment in the commercial banks through training of the neural network tools and testing. Empirical results and analysis indicate that this kind of method has the satisfied assessment efficiency and theoretical accuracy and is applicable to Chinese commercial banks.

Published in:

Information Technology and Applications, 2009. IFITA '09. International Forum on  (Volume:1 )

Date of Conference:

15-17 May 2009