Research on the Sample Training of BP Neural Network in Effectiveness Evaluation

摘要：

According to the WSEIAC (Weapon System Effectiveness Industry Advisory Committee) model, an index hierarchy of ground antiaircraft missile weapon systems effectiveness has been developed, and corresponding three hierarchy BP neural network was established. It is briefly concerned with the analysis of the BP algorithm, then through Delphi technique and the FAHP (Fuzzy Analytical Hierarchy Process), several groups of training samples are chosen to train the BP neural networks until the precision meet requirements. It is shown that this BP neural network limits the artificial factors when it is used to evaluate the ground antiaircraft missile weapon systems effectiveness. It was concluded that this method is scientific and creditable.

关键词： BP neural networks sample training effectiveness evaluation WSEIAC

作者: Yanbin SHI An ZHANG Jian GUO

作者单位: College of Electronic and Information Northwestern Polytechnical University Xian 710072, China College of Information Engineer Urumqi Vocational University Urumqi 830002, China

会议类型: 国际会议

会议名称: 第三届IEEE无线通讯、网络技术暨移动计算国际会议

会议地点: 上海

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）