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

页码：410 / 414

页数：5

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