A data mining based genetic algorithm

Yi Ta Wu, Yoo Jung An, James Geller, Yih Tyng Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Genetic algorithms (GAs) are considered as a global search approach for optimization problems. Through the proper evaluation strategy, the best "chromosome" can be found from the numerous genetic combinations. Although the GA operations do provide the opportunity to find the optimum solution, they may fail in some cases, especially when the length of a chromosome is very long. In this paper, a data mining-based GA is presented to efficiently improve the Traditional GA (TGA). By analyzing support and confidence parameters, the important genes, called DNA, can be obtained. By adopting DNA extraction, it is possible that TGA will avoid stranding on a local optimum solution. Furthermore, the new GA operation, DNA implantation, was developed for providing potentially high quality genetic combinations to improve the performance of TGA. Experimental results in the area of digital watermarking show that our data mining-Jbased GA successfully reduces the number of evolutionary iterations needed to find a solution.

Original languageEnglish (US)
Title of host publicationProc. - The Fourth IEEE Workshop on Software Technol. for Future Embedded and Ubiquitous Systems, SEUS 2006 andthe Second Int. Workshop on Collaborative Computing, Integr., and Assurance, WCCIA 2006
Pages55-60
Number of pages6
DOIs
StatePublished - Nov 16 2006
Event4th IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, SEUS 2006 andthe 2nd International Workshop on Collaborative Computing, Integration, and Assurance, WCCIA 2006 - Gyeongju, Korea, Republic of
Duration: Apr 27 2006Apr 28 2006

Publication series

NameProc. - The Fourth IEEE Workshop on Software Technol. for Future Embedded and Ubiquitous Syst., SEUS 2006 andthe Second Int. Workshop on Collaborative Comput., Integr., and Assur., WCCIA 2006
Volume2006

Other

Other4th IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, SEUS 2006 andthe 2nd International Workshop on Collaborative Computing, Integration, and Assurance, WCCIA 2006
CountryKorea, Republic of
CityGyeongju
Period4/27/064/28/06

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Keywords

  • Data mining
  • Digital watermarking
  • Evolutionary algorithm
  • Genetic algorithm

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