Study on the early-warning model of logistics outsourcing risk based on rough sets theory and BP neural network

摘要：

In the process of logistics outsourcing, there are a lot of uncertain factors which may cause all kinds of potential risks and impact the realization of corporate decision-making goals The paper proposed a logistics outsourcing risk early-warning model based on rough sets theory and BP neural network, on the basis of identifying the assessment indicators of logistics outsourcing risk, the paper established the decision table of logistics outsourcing risk early-warning, used Johnson Reducer algorithm to reduce the initial decision table, and took the attributes after the reduction as the inputs of BP neural network, which speeded up the training speed of neural network. At the same time, the paper carried out logistics outsourcing risk early-warning on five enterprises in Handan and the results showed the effectiveness of the proposed early-warning model.

关键词： logistics outsourcing risk early-warning rough sets theory neural network

作者: Hua JIANG

作者单位: School of Economics and Management,Hebei University of Engineering,056038,China

会议类型: 国际会议

会议名称: 2008 International Conference on Risk and Relianility Management(2008风险与可靠性管理国际会议)

会议地点: 北京

会议语种:英文

页码: 386-391

在线出版日期: 2008-11-10（万方平台首次上网日期，不代表论文的发表时间）