摘要
利用一种新的人工智能方法———GA-PSO混合规划算法构建企业信用风险评估模型。并利用上证50若干企业的实际数据对模型进行了实证检验。实证结果显示该模型能有效预测上市企业的信用风险状况。该模型在收敛性能及预测准确率等方面优于基于传统的多元回归方法及GP方法的信用风险评估模型。
The paper is meant to set up a enterprise credit risk evaluation model by a new AI method-GA-PSO optimize algorithm. We tested the model by using the data of so companies of the stock Market of Shanghai. The result shows that this model can predict the listed companies credit risk effectively. It is superior to traditional Multipie Regression＇s calculating model and GP in model＇s astringency and predict accuracy.
出处
《西北大学学报（哲学社会科学版）》
CSSCI
北大核心
2006年第3期38-40,共3页
Journal of Northwest University：Philosophy and Social Sciences Edition
基金
陕西省科学技术研究发展计划基金资助项目(2004KR55)
