Title :
The Application of WN Based on PSO in Bank Credit Risk Assessment
Author :
Zhaoji, Yu ; Qiang, Mao ; Wenjuan, Wang
Author_Institution :
Sch. of Manage., Shenyang Univ. of Technol., Shenyang, China
Abstract :
The purpose of this paper is enhancing the quality of credit rating in e-business environment and reducing credit risk. The principle of the particle swarm optimization(PSO) algorithm and wavelet networks(WN) model, propose implementation steps of the WN based PSO. The algorithm is applied to the credit risk evaluating for bank, and its result is compared with conventional wavelet networks. The comparing result shows that the WN based PSO fits to complex system such as credit evaluating for bank, it improves in a certain extent on training speed and precision, it can improve the quality of bank credit risk, and it fits to solve some problems in which evaluating indexes weights are difficult to be determined or there exists complex non-linear relation among them.
Keywords :
banking; conjugate gradient methods; particle swarm optimisation; radial basis function networks; risk management; wavelet transforms; PSO; WN; bank credit risk assessment; conjugate gradient algorithm; particle swarm optimization algorithm; wavelet network theory; wavelet networks model; Artificial neural networks; Companies; Convergence; Indexes; Particle swarm optimization; Training; Wavelet transforms; credit risk; evaluating; particle swarm optimization; wavelet networks;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.331
