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基于遗传算法的乙烯生产装置神经网络模型的建立
引用本文:王景芳.基于遗传算法的乙烯生产装置神经网络模型的建立[J].石油化工自动化,2006(1):48-51.
作者姓名:王景芳
作者单位:湖南涉外经济学院,信息与电子工程系,湖南,长沙,410205
摘    要:基于遗传算法建立乙烯生产装置神经网络模型;先依据乙烯生产装置工况间的非线性程度设计人工神经网络模型结构.再用遗传算法对该网络模型参数进行组合优化确定,所建模型既可用来进行乙烯产率预测,亦可用来对其生产工况优化,示例表明;建好后的网络模型可对乙烯生产装置进行快速工艺参数优化,获得较优的操作数据。

关 键 词:乙烯生产装置  遗传算法  神经网络  建模  非线性  组合优化
文章编号:1007-7324(2006)01-0048-04
修稿时间:2005年6月22日

Establishment of Neural Network Mode for Ethylene Plant Based on the Genetic Algorithms
Wang Jingfang.Establishment of Neural Network Mode for Ethylene Plant Based on the Genetic Algorithms[J].Automation in Petro-chemical Industry,2006(1):48-51.
Authors:Wang Jingfang
Abstract:How to establish the neural network modes of ethylene plant based on genetic algorithms is introduced;first of all,the artificial neural network model structure has been designed according to the nonlinear degree between ethylene plant iostances and optimized any longer the network model parameters by use of Genetic Algorithms.This model is used to forecast the ethylene yield ratio and also to optimize the productive operation.An example showed that the process parameters of the ethylene plant can be speedily optimized by the genetic network model,and higher ethylene yield can be obtained.
Keywords:ethylene plant  genetic algorithms  neural network  model  nonlinear  combination optimization
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