基于BP神经网络的制造业上市公司财务预警  

Financial Crisis Warning Research Of Manufacturing Industry Based on BP Neural Network

作　　者：张根明[1] 向晓骥[1] 孙敬宜[2] 

机构地区：[1]中南大学商学院,长沙410083 [2]烟台职业学院经济系,山东烟台250000

出　　处：《山东工商学院学报》2006年第4期56-61,共6页Journal of Shandong Technology and Business University

摘　　要：采用BP神经网络方法,以263家制造业上市公司的截面财务指标作为学习样本,并使用76家制造业上市公司作为检验样本,建立了制造业上市公司财务预警模型。其研究结果表明与没有区分行业的通用预警模型相比,分行业的BP神经网络财务预警模型的预测精度有了较大提高,为广大投资者和监管机构预测公司财务状况提供了可靠的依据。The paper uses the BP artificial neural network to establish a financial crisis warning model. The model consists of the cross section financial indexes of 263 listed companies in the manufacture industry as study samples, and 76 companies are used as testing samples. The study indicates that compared with previous research that do not differentiate industry, BP fields financial crisis warning model is more accurate in forecasting, provide a useful tool for investors and regulaters. So BP is a relatively good method for analyzing and forecasting financial conditions, with wide applying area and high value of popularizing.

关 键 词：财务预警 人工神经网络 制造业上市公司 预警模型 

分 类 号：F426.4[经济管理—产业经济]