Research on the Forecasting of Inventory Risk Management of Spare Parts: A Neural Network Model

摘要：

This paper proposes a neural network-based classification approach to inventory risk level of spare parts. Firstly a fuzzy, evaluation of spare parts is made in terms of their availability of suppliers, importance, predictability of failure, specificity and lead time. Then a multilayer feed forward neural network model is established. The Back Propagation (BP) algorithm for training a neural network is used to decide the weights to connections in the model. Choosing a sample of historical data of 100 spare parts and undertaking a BP training stimulation, the model is used to predict the inventory risk levels of 60 spare parts for a welllogging service firm. The forecasting reliability reaches 84％.

关键词： management of spare parts neural network back propagation algorithm

作者: Weipeng WANG

作者单位: School of Economics and Management Weifang University Weifang, China

会议类型: 国际会议

会议名称: The 13th IEEE Joint International Computer Science and Information Technology Conference(2011年第13届IEEE联合国际计算机科学与信息技术会议 JICSIT 2011)

会议地点: 重庆

会议语种:英文

页码: 980-983

在线出版日期: 2011-08-20（万方平台首次上网日期，不代表论文的发表时间）