Notice of Retraction: Chaotic clonal genetic algorithm for protein folding model

Yudong Zhang, Lenan Wu*, Yuankai Huo, Shuihua Wang

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)

Abstract

To IMPROVE PROTEIN FOLDING SIMULATIONS, A NOVEL CHAOTIC CLONAL GENETIC ALGORITHM (CCGA) WAS INVESTIGATED ON A 2D LATTICE MODEL. THE NOVEL ALGORITHM COMBINES CHAOS OPERATOR, CLONAL SELECTION ALGORITHM, AND GENETIC ALGORITHM. WE COMPARED CCGA WITH STANDARD GENETIC ALGORITHM (SGA) AND IMMUNE GENETIC ALGORITHM (IGA) FOR VARIOUS CHAIN LENGTHS. IT HAS SHOWN THAT CCGA NOT ONLY FIND GLOBAL MINIMA MORE RELIABLY, BUT ALSO BE SIGNIFICANTLY FASTER IN CONVERGENCE.

Original languageEnglish
Title of host publicationICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings
PublisherIEEE Computer Society
PagesV3120-V3124
ISBN (Print)9781424472369
DOIs
Publication statusPublished - 2010
Externally publishedYes

Publication series

NameICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings
Volume3

Keywords

  • Chaotic clonal genetic algorithm
  • Protein folding model

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