DocumentCode
501364
Title
Notice of Retraction
An Application of the Combination of Principal Component Analysis and BP Neural Network to Credit Assessment in the Commercial Banks
Author
Li Bo ; Xu Congwei
Author_Institution
Sch. of Econ. & Manage., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
Volume
1
fYear
2009
fDate
15-17 May 2009
Firstpage
426
Lastpage
429
Abstract
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.
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.
Keywords
backpropagation; bank data processing; credit transactions; forecasting theory; neural nets; principal component analysis; risk management; BP neural network; biology nerve cell; combination forecasting; commercial banks; credit risk assessment; credit risk management; principal component analysis; Cells (biology); Economic indicators; Eigenvalues and eigenfunctions; Information technology; Input variables; Joining processes; Neural networks; Principal component analysis; Risk management; Standardization;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location
Chengdu
Print_ISBN
978-0-7695-3600-2
Type
conf
DOI
10.1109/IFITA.2009.90
Filename
5231648
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