| 基于一种改进的自适应遗传算法估算环已烷自催化氧化反应动力学参数 |
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| 引用本文： | 刘平乐,邹丽珊,罗和安,王良芥,郑金华. 基于一种改进的自适应遗传算法估算环已烷自催化氧化反应动力学参数[J]. 中国化学工程学报, 2004, 12(1): 49-54 |
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| 作者姓名： | 刘平乐 邹丽珊 罗和安 王良芥 郑金华 |
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| 作者单位： | [1]CollegeofChemicalEngineering,XiangtanUniversity,Xiangtan411105,China [2]CollegeofInformationEngineeringandTechnology,XiangtanUniversity,Xiangtan411105,China |
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| 摘 要： | A modified genetic algorithm of multiple selection strategies, crossover strategies and adaptive operator is constructed, and it is used to estimate the kinetic parameters in autocatalytic oxidation of cyclohexane. The influences of selection strategy, crossover strategy and mutation strategy on algorithm performance are discussed. This algorithm with a specially designed adaptive operator avoids the problem of local optimum usually associated with using standard genetic algorithm and simplex method. The kinetic parameters obtained from the modified genetic algorithm are credible and the calculation results using these parameters agree well with experimental data. Furthermore, a new kinetic model of cyclohexane autocatalytic oxidation is established and the kinetic parameters are estimated by using the modified genetic algorithm.
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| 关 键 词： | 环己胺 自身催化氧化 适应遗传算法 反应动力学 |
| 修稿时间： | |
Estimation of Kinetic Parameters for Autocatalytic Oxidation of Cyclohexane Based on a Modified Adaptive Genetic Algorithm |
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| LIU Pingle,ZOU Lishan,LUO He''an,WANG Liangjie,ZHENG Jinhua. Estimation of Kinetic Parameters for Autocatalytic Oxidation of Cyclohexane Based on a Modified Adaptive Genetic Algorithm[J]. Chinese Journal of Chemical Engineering, 2004, 12(1): 49-54 |
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| Authors: | LIU Pingle ZOU Lishan LUO He''an WANG Liangjie ZHENG Jinhua |
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| Affiliation: | College of Chemical Engineering, Xiangtan University,Xiangtan 411105, China College of Information Engineering and Technology, Xiangtan University,Xiangtan 411105, China |
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| Abstract: | A modified genetic algorithm of multiple selection strategies, crossover strategies and adaptive operator is constructed, and it is used to estimate the kinetic parameters in autocatalytic oxidation of cyclohexane. The influences of selection strategy, crossover strategy and mutation strategy on algorithm performance are discussed.This algorithm with a specially designed adaptive operator avoids the problem of local optimum usually associated with using standard genetic algorithm and simplex method. The kinetic parameters obtained from the modified genetic algorithm are credible and the calculation results using these parameters agree well with experimental data.Furthermore, a new kinetic model of cyclohexane autocatalytic oxidation is established and the kinetic parameters are estimated by using the modified genetic algorithm. |
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| Keywords: | adaptive genetic algorithm cyclohexane autocatalytic oxidation reaction kinetics |
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