Paper Title:
Application of Chaos Particle Swarm Optimized Neural Networks for Evaluating the Credit Risk
  Abstract

This paper proposes a hybrid algorithm based on chaos optimization and particle swarm optimization (PSO) to improve the performance of the neural networks (NN) on evaluating credit risk. The hybrid algorthm not only maintains the advantage of simple structure, but also improves the convergence of the traditional PSO algorithm, and enhances the global optimization capability and accuracy of the algorithm. The test results indicate that the performance of the proposed model is better than the ones of NN model using the BP algorithm and traditional PSO algorithm.

  Info
Periodical
Key Engineering Materials (Volumes 460-461)
Edited by
Yanwen Wu
Pages
687-691
DOI
10.4028/www.scientific.net/KEM.460-461.687
Citation
Z. B. Xiong, "Application of Chaos Particle Swarm Optimized Neural Networks for Evaluating the Credit Risk", Key Engineering Materials, Vols. 460-461, pp. 687-691, 2011
Online since
January 2011
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