基于BP 神经网络的我国石化类上市公司经营风险预警系统

Early Warning System of Operational Risks in Petrochemical Listed Companies in China Based on BP Artificial Neural Network

摘要: 上市公司作为推动完善我国市场经济发展体制以及我国经济发展方式转变的重要动力之一，在历经多年的发展磨练之后，其经营监管模式已日渐完善。但，在尚未完全退去的这场金融危机中，我国上市公司对风险的预知与判断能力之薄弱业已完全显露。故本文以国民经济发展支柱型产业石化类上市公司作为研究对象，运用BP 神经网络模型作为支撑，借助于Matlab 提供的运算平台，构建适应于公司经营风险的预警系统。通过所截取研究样本的实际数据验证表明：本文所构建的经营风险预警系统，实现了对我国石化类上市公司经营风险的有效预测与判断，具有一定的实践应用价值。

Abstract: Listed Company is one of the important power in perfecting our market economy system and in promoting transformation of the pattern of economic development. After many years of development, its business and regulatory model has improved. But in the financial crisis, the weakness of listed company exposed completely. It’s lack of the ability to predict and judge the business risk. Using the BP neural network model on Matlab, so the thesis constructs the business risk warning system based on the data from the petrochemical listed company, which is the pillar industry in our national economy development. The results show that the constructed business risk warning system realizes effective prediction and judge of business risk in the petrol chemical listed company in China; it has certain practical application value.