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基于遗传算法与人工神经网络相结合的固体推进剂燃速计算
引用本文:代志龙,张小平,胡润芝.基于遗传算法与人工神经网络相结合的固体推进剂燃速计算[J].计算机与应用化学,2006,23(7):639-642.
作者姓名:代志龙  张小平  胡润芝
作者单位:中国航天科技集团公司四院四十二所,湖北,襄樊,441003
摘    要:为了提高固体推进剂燃速预示精度,将遗传算法(Genetic Algorithm)与误差反传(Back Propagation)网络结构模型相结合,设计了用遗传算法优化神经网络权重的新方法。以固体推进剂燃速数据库为基础,对推进剂的燃速进行了预估,并与BP算法进行了比较。结果显示,预估值与实际值接近,误差小于BP算法模型,具有良好的预示效果,为推进剂燃速预估提供了新方法。

关 键 词:推进剂燃速预估  遗传算法  神经网络
文章编号:1001-4160(2006)07-639-642
收稿时间:2005-08-21
修稿时间:2005-08-212006-01-15

Calculate for burning rate of solid propellant based on combination of genetic algorithm and back-propagation neural networks
Dai Zhilong,Zhang Xiaoping,Hu Runzhi.Calculate for burning rate of solid propellant based on combination of genetic algorithm and back-propagation neural networks[J].Computers and Applied Chemistry,2006,23(7):639-642.
Authors:Dai Zhilong  Zhang Xiaoping  Hu Runzhi
Affiliation:The 42nd Institute of the Fourth Academy of CASC, Xiangfan, 441003, Hubei, China
Abstract:In order to improve predicting precision of burning-rate of solid propellant.Combine Genetic Algorithm and Back-Propagation neural network,A fresh method on optimizing biases and weights of neural networks by Genetic Algorithm was demonstrated.Based on the database of solid propellants.Burning rate of solid propellant was predicted and contrasted to BP.The result showed that calcula- tions were corresponding to practice and the errors were smaller than BP.So it supplies a new method for predicting burning rate of sol- id propellant.
Keywords:predicting of burning rate of solid propellant  genetic algorithm  neural network
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