Ammunition Storage Reliability Forecasting Based on Radial Basis Function Neural Network

摘要：

　　In order to forecast ammunition storage reliability better,the paper researched a forecasting method based on neural network which is with the ability of actualizing multi-nonlinear mapping from input to output,and discussed steps of forecasting based on radial basis function (RBF) network.The storage reliability of one new-style ammunition is forecasted based on RBF network.The results show that RBF is suitable for ammunition storage reliability forecasting,and the precision of the train goal is better by using RBF network than by using BP network.RBF network is more suitable for dealing with this problem.

关键词： ammunition storage reliability forecasting radial basis function neural network

作者: Jiang Liu Dan Ling Song Wang

作者单位: Unit 78618 of Peoples Liberation Army Chengdu, P. R. China;School of Mechatronics Engineering Unive School of Mechatronics Engineering University of Electronic Science and Technology of China Chengdu,

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: 598-601

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）