• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

author:

Zhao, Chao (Zhao, Chao.) [1] (Scholars:赵超) | An, Aimin (An, Aimin.) [2] | Xu, Qiaolin (Xu, Qiaolin.) [3] (Scholars:许巧玲)

Indexed by:

EI Scopus

Abstract:

The determination of the optimal model parameters for kinetic systems development of kinetic models is a time consuming, iterative process [1]. In this paper, we presented a novel hybrid Differential Evolution (DE) algorithm for solving kinetic parameter estimation problems based on the Differential Evolution technique together with a local search strategy. By combining the merits of DE with Gauss-Newton method, the proposed hybrid approach employs a DE algorithm for identifying promising regions of the solution space followed by use of Gauss-Newton method to determine the optimum in the identified regions. The computational results indicate that the global searching ability and the convergence speed of this hybrid algorithm are significantly improved. Additionally, study of kinetic model parameters for an irreversible, first-order reaction system was carried out to test the applicability of the proposed algorithm. The suggested method can be used to estimate suitable values for the model parameters of a complex mathematical model. © 2012 IEEE.

Keyword:

Evolutionary algorithms Kinetic parameters Kinetic theory Newton-Raphson method Optimization Parameter estimation

Community:

  • [ 1 ] [Zhao, Chao]Faculty of College of Chemistry and Chemical Engineering, FuZhou University, FuZhou, 350108, China
  • [ 2 ] [An, Aimin]Faculty of School of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu 730050, China
  • [ 3 ] [Xu, Qiaolin]Faculty of College of Chemistry and Chemical Engineering, FuZhou University, FuZhou, 350108, China

Reprint 's Address:

Show more details

Version:

Related Keywords:

Related Article:

Source :

Year: 2012

Page: 1696-1700

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

Online/Total:72/10115162
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1