CIESC Journal

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混沌遗传算法估计反应动力学参数

颜学峰; 陈德钊; 胡上序; 丁军委   

  1. 浙江大学化学工程与生物工程学系
  • 出版日期:2002-08-25 发布日期:2002-08-25

ESTIMATION OF KINETIC PARAMETERSUSING CHAOS GENETIC ALGORITHMS

YAN Xuefeng;CHEN Dezhao;HU Shangxu;DING Junwei   

  • Online:2002-08-25 Published:2002-08-25

摘要: 为了准确地估计反应动力学参数 ,提出一种混沌遗传算法 (chaosgeneticalgorithm ,CGA) ,它基于混沌变量的遗传操作 ,将使子代个体均匀地分布于定义空间 ,从而可避免早熟 ,以较大的概率实现全局最优搜索 .与传统的遗传算法相比较 ,CGA的在线和离线性能都有较大的改进 .将CGA应用于 2 -氯苯酚在超临界水中氧化反应动力学参数的估算 ,获得了满意的结果

Abstract: As the individual distribution of linear crossover operator in real-coded tradit ional genetic algorithm (GA) tends to approach the center of defined space with the searching process,a novel genetic algorithm,which is named as chaos genetic algorithm (CGA),is proposed.Its genetic operation,which is based on chaos variable,makes the individuals of subgeneration distribut e uniformly in the defined space and avoids the premature of subgeneration.To co mpare the performances of the CGA with those of the traditional GA,the CGA and the traditional GA were applied to estimate the kinetic parameters of 2-chloroph eol oxidation in supercritical water under the same condition.The results demon strated that the CGA’s on-line and off-line performance was all superior t o that of the traditional GA,and that the probability of finding global optimal solution was larger than that of the traditional GA.Thus,due to the good perfo rmances of the CGA and the drawbacks of the premature nature and the finding par t optimal solution of the traditional GA,the CGA is an attractive alternative t o the traditional GA.