The Launch System Life Prediction Based on Optimized Grey Neural Network Model by Particle Swarm

被引：0

作者：

Wang, Wenfeng ^{[1
]}

Zhang, Lin ^{[1
]}

Wang, Jun ^{[1
]}

Sun, Anquan ^{[1
]}

机构：

[1] AFEU Shanxi, Air & Missile Def Coll, Xian 710051, Shaanxi, Peoples R China

来源：

ELECTRICAL AND CONTROL ENGINEERING & MATERIALS SCIENCE AND MANUFACTURING | 2016年

基金：

美国国家科学基金会;

关键词：

Gray System; Neural Network; Particle Swam Optimization; Life Prediction;

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：

In order to ensure an accurate prediction of the life of the transmission system, a gray BP neural network model is created. Flexible rate adjustment factor and adaptive inertia factor are introduced to improve the optimization performance of the particle swarm optimization. Once more, the gray BP neural network model is optimized by the particle swarm optimization. Finally-, the prediction model is trained for the optimal solution. Simulation results show that this method gets good convergence rate while improving the prediction accuracy.

引用

页码：33 / 38

页数：6

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