SCI和EI收录∣中国化工学会会刊

›› 2009, Vol. 17 ›› Issue (2): 232-240.

• • 上一篇    下一篇

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

胡春平, 颜学峰   

  1. Automation Institute, East China University of Science and Technology, Shanghai 200237, China
  • 收稿日期:2008-07-28 修回日期:2008-12-24 出版日期:2009-04-28 发布日期:2009-04-28
  • 通讯作者: YAN Xuefeng,E-mail:yan_xuefeng@hotmail.com
  • 基金资助:
    Supported by the National Natural Science Foundation of China (20506003,20776042);the National High-Tech Research and Development Program of China (2007AA04Z164)

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

HU Chunping, YAN Xuefeng   

  1. Automation Institute, East China University of Science and Technology, Shanghai 200237, China
  • Received:2008-07-28 Revised:2008-12-24 Online:2009-04-28 Published:2009-04-28
  • Supported by:
    Supported by the National Natural Science Foundation of China (20506003,20776042);the National High-Tech Research and Development Program of China (2007AA04Z164)

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 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.

关键词: differential evolution, immune system, evolutionary computation, parameter estimation

Abstract: 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.

Key words: differential evolution, immune system, evolutionary computation, parameter estimation