BP neural network optimized by PSO algorithm on Ammunition storage reliability prediction

被引：0
|
作者：
Gong, Hua [1 ]
Zhang, Ermei [1 ]
Yao, Jun [1 ]
机构：
[1] Shenyang Ligong Univ, Coll Sci, Shenyang, Liaoning, Peoples R China
来源：
2017 CHINESE AUTOMATION CONGRESS (CAC) | 2017年
关键词：
PSO; BP neural network; prediction; Storage reliability;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Storage reliability of the ammunition dominates the efforts in achieving the mission reliability goal. Prediction of storage reliability is important in practice to monitor the ammunition quality. In this paper we provided an integrated method where particle swarm optimization (PSO) algorithm is applied to adjust and optimize the BP neural network global parameters (weights and thresholds). The experiment results show that PSO-BP algorithm can achieve the convergence rate and increase the prediction accuracy of storage reliability.
引用
收藏
页码：692 / 696
页数：5
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