文献类型：期刊文献

中文题名：An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation

英文题名：An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation

作者：Hu Chunping[1];Yan Xuefeng[1]

机构：[1]E China Univ Sci & Technol, Automat Inst, Shanghai 200237, Peoples R China

年份：2009

卷号：17

期号：2

起止页码：232

中文期刊名：Chinese Journal of Chemical Engineering

外文期刊名：CHINESE JOURNAL OF CHEMICAL ENGINEERING

收录：CSTPCD;;EI(收录号：20092012080651);Scopus;WOS:【SCI-EXPANDED(收录号:WOS:000265757000009)】；CSCD:【CSCD2011_2012】；

基金：Supported by the National Natural Science Foundation of China (20506003, 20776042) and the National High-Tech Research and Development Program of China (2007AA04Z164).

语种：英文

中文关键词：differential evolution; immune system; evolutionary computation; parameter estimation

外文关键词：differential evolution; immune system; evolutionary computation; parameter estimation

摘要：A new version of differential evolution （DE） algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution （ISDE）, is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters＇ self-adaptation. The .performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm ~nd-other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury. （Hg） oxidation in flue gas, and satisfactory results are obtained.
A new version of differential evolution (DE) algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution (ISDE), is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters' self-adaptation. The performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm and other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury (Hg) oxidation in flue gas, and satisfactory results are obtained.