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

胡春平; 颜学峰

doi:10.1016/S1004-9541(08)60199-8

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

Updated：2026-01-06

- An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation
- An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation
- 中国化学工程学报（英文版） 2009年17卷第2期页码：232-240
- Affiliations：
  
  Automation Institute, East China University of Science and Technology,Shanghai,China,200237
- Author bio：
- Funds：
  
  Supported by the National Natural Science Foundation of China (20506003,20776042);the National High-Tech Research and Development Program of China (2007AA04Z164)
- DOI：10.1016/S1004-9541(08)60199-8
  中图分类号：
- 纸质出版：2009
- Accepted：
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胡春平, 颜学峰. An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation[J]. 中国化学工程学报（英文版）, 2009,17(2):232-240.

HU Chunping, YAN Xuefeng. An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation[J]. , 2009, 17(2): 232-240.
胡春平, 颜学峰. An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation[J]. 中国化学工程学报（英文版）, 2009,17(2):232-240. DOI： 10.1016/S1004-9541(08)60199-8.

HU Chunping, YAN Xuefeng. An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation[J]. , 2009, 17(2): 232-240. DOI： 10.1016/S1004-9541(08)60199-8.

摘要

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.

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