Equipment Spare Parts Demand Forecasting Model Based on Grey Neural Network

摘要：

　　Equipment spare parts demand forecasting is the precondition of conducting effective spare parts supporting.Equipment spare parts demand change is the result of comprehensive factors and single model forecasting accuracy is not high.Aim to improve the precision of equipment spare parts demand forecasting,a forecasting method of equipment spare parts demand is proposed using grey neural network based on analyzing the main factors influencing spare parts wastage synthetically.The proposed method uses the grey forecasting model to train the training samples and gets the BP neural network input value,then BP neural network is used to get the equipment spare parts demand results.Simulation results demonstrate that the proposed method has higher forecasting precision compared with single forecasting model,which verifies the correctness and efficiency of the proposed method.

关键词： gray neural network spare parts demand demand forecasting

作者: Hui Song Cheng Zhang Guangyu Liu Wukui Zhao

作者单位: The 6th Department Shijiazhuang Mechanical Engineering College Shijiazhuang, Hebei, China

会议类型: 国际会议

会议名称: 2012 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering & The 3rd International Conference on Maintenance Engineering (2012质量,可靠性,风险,维修性及安全性工程国际会议(QR2MSE 2012 & ICME 2012))

会议地点: 成都

会议语种:英文

页码: 1280-1283

在线出版日期: 2012-06-15（万方平台首次上网日期，不代表论文的发表时间）