Individual Credit Risk Assessment Studies Based on PSO-RBF Neural Network

被引：0

作者：

Zhu, Yuanmei ^{[1
]}

Li, Shuai ^{[1
]}

Zhou, Zongfang ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Management & Econ, Chengdu 610054, Peoples R China

来源：

INNOVATIVE THEORIES AND METHODS FOR RISK ANALYSIS AND CRISIS RESPONSE | 2012年 / 21卷

关键词：

individual credit risk assessment; PSO algorithm; RBF neural network; PSO-RBF model;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In order to establish a more applicable individual credit risk assessment model,a PSO-RBF neural network model is constructed,in which the parameters of RBF are trained by PSO algorithm. In this model the global searching capability of PSO and the local optimization efficiency of RBF are combined to overcome the instability of PSO and the shortcoming that trapped into local minimal easily of RBF. The application results indicate that PSO-RBF has an advantage in classification accuracy and assessment accuracy. Therefore, PSO-RBF applies to individual credit risk assessment, showing a good application value.

引用

页码：493 / 498

页数：6