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基于PSO-BP神经网络的企业信用风险评估模型研究
引用本文:董槐林,郭阳,郑宇辉.基于PSO-BP神经网络的企业信用风险评估模型研究[J].计算机与现代化,2009(4).
作者姓名:董槐林  郭阳  郑宇辉
作者单位:厦门大学软件学院,福建,厦门361005
摘    要:企业信用风险评估是金融领域的重要课题.本文针对单独运用BP神经网络评估信用风险时存在的不足,提出了一种基于PSO-BP神经网络的企业信用风险评估模型.该模型首先应用主成分分析方法降低输入BP网络的信用评估指标维数,并且采用粒子群优化算法优化BP神经网络的权值.实验表明,新模型采用的算法具有收敛速度快,预测精度高的优点,是一种有效可靠的企业信用风险评估模型.

关 键 词:信用风险评估  主成分分析  粒子群优化算法  BP神经网络

Study of Credit Risk Assessment of Enterprise Based on PSO-BP Neural Network
DONG Huai-lin,GUO Yang,ZHENG Yu-hui.Study of Credit Risk Assessment of Enterprise Based on PSO-BP Neural Network[J].Computer and Modernization,2009(4).
Authors:DONG Huai-lin  GUO Yang  ZHENG Yu-hui
Affiliation:Software School;Xiamen University;Xiamen 361005;China
Abstract:Credit risk assessment of enterprise is a very important problem in the financial field.Its deficiency is revealed because of singly using BP neural network.In this paper,a new assessment model is proposed which is based on an optimized BP neural network.In this model,first,dimensions of data are reduced by Principal Component Analysis(PCA);Second,Particle Swarm Optimization(PSO) is used for optimizing parameters of neural network.The experiment results show that PSO-BP algorithm works with quicker converge...
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