基于模糊神经网络的企业财务危机非线性组合预测方法研究  

Research on Forecasting Firms Financial Distress Based on Nonlinear Combining of Fuzzy Neural Network

作　　者：李秉祥[1] 

机构地区：[1]西安交通大学应用经济学博士后流动站

出　　处：《管理工程学报》2005年第1期19-23,共5页Journal of Industrial Engineering and Engineering Management

基　　金：国家自然科学基金资助项目(70372053)

摘　　要：本文提出了一种基于模糊神经网络的企业财务危机非线性组合建模与预测新方法,并给出了相应的混合学习算法。通过与多元线性回归模型、Fisher模型和Logistic回归模型的预测结果对比表明,该方法具有预测精度高,学习与泛化能力强,适应性广的优点。在预测上市公司财务危机方面优于其他方法。This paper presents a new nonlinear composite forecasting method for corporate financial distress modeling and forecasting based on fuzzy neural network,and gives the corresponding composite learning algorithm. It has been shown that the method has more accurate forecasts,reinforcement learning properties and mapping capabilities by comparing with LPM,Fisher model and Logistic model. The method is better than others ones in forecasting financial distress in listed firms.

关 键 词：财务危机 组合预测 多元线性分析 模糊神经网络 

分 类 号：F275[经济管理—企业管理]