A New Model of Enterprise Credit Risk Assessment Based on BP Neural Network

被引：0
|
作者：
Guo Yang [1 ]
Dong Huailin [1 ]
Zheng Yuhui [1 ]
Wu Junjie [1 ]
Wu Jing [1 ]
机构：
[1] Xiamen Univ, Software Sch, Xiamen 361005, Fujian, Peoples R China
来源：
ICCSE 2008: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION: ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION | 2008年
关键词：
Credit risk assessment; BP neural network; Principal component analysis (PCA); Quantum-behaved particle swarm optimization (QPSO);
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Enterprise credit risk assessment is a very important problem in the financial field. Its deficiency was 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 were reduced by principal component analysis (PCA); second, Quantum-behaved particle swarm optimization (QPSO) was used for optimizing parameters of BP neural network. The experiment results show that the new model reduces the training time and has a very small error; it can satisfy the demand of credit risk assessment of enterprise.
引用
收藏
页码：410 / 414
页数：5
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