Research and application of PSO-BP Neural Networks in Credit Risk Assessment

摘要：

According to the complexity of financial system, the model of credit risk assessment based on PSO algorithm and BP neural network integrated is proposed, which in order to improve the accuracy and reliability of risk assessment First the neural network model of a credit risk evaluation is created, and then PSO algorithm is introduced to optimize the weight and threshold of the neural network, at last, using the indexes and regarding relevant data of 250 enterprises as samples, the BP neural network is trained and tested. Compared with the traditional calculation methods, experimental results show that the method is a feasible and effective assessment method with fast convergence and high precision prediction.

关键词： credit risk risk assessment BP neural network particle swarm optimization

作者: Ning LIU En-jun XIA Li YANG

作者单位: The School of Management and Economics Beijing Institute of echnology Beijing, China The School of Management and Economics Beijing Institute of Technology Beijing, China Party School of CPC SiShui County Committee Jining, China

会议类型: 国际会议

会议名称: 2010 International Symposium on Computational Intelligence and Edsign(第三届计算智能与设计国际学术研讨会 ISCID 2010)

会议地点: 杭州

会议语种:英文

页码: 103-106

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）