The Research on the Consuming Prediction of Military Aircraft Spare Parts

摘要：

　　Aiming at the problem that the consuming-related factors of military aircrafts spare parts cant be revealed in the model,support vector machines (SVM) model was applied in the consuming prediction of spare parts,in the model,the main factors that affected spare parts consumption were taken as the input of SVM while the output was the consumption.Then,the test samples were input the trained model for prediction.The results show that,compared with GM (1,1) model and neural network model(ANN),the model has higher prediction accuracy and dynamic adaptability,which can provide some reference for the spare parts management sections.

关键词： spare parts support vector machines consuming prediction

作者: De-xiang Sun Sheng-quan Tang Guo-ping Xing Xiao-kun Wang Yong-yu Liu

作者单位: Flight Institute Aviation University of Air Force Changchun,China Aircraft & Engine Department Aviation University of Air Force Changchun,China

会议类型: 国际会议

会议名称: 2013 2nd international Conference on Opto-Electronics Engineering and Materials Eesearch(2013第二届光电工程与材料研究国际会议)(OEMR2013)

会议地点: 郑州

会议语种:英文

页码: 1586-1590

在线出版日期: 2013-10-19（万方平台首次上网日期，不代表论文的发表时间）