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Symbiotic evolution to avoid linkage problem

Halavati, R ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-540-85068-7_12
  3. Publisher: 2008
  4. Abstract:
  5. In this chapter, we introduce Symbiotic Evolutionary Algorithm (SEA) as a template for search and optimization based on partially specified chromosomes and symbiotic combination operator. We show that in contrast to genetic algorithms with traditional recombination operators, this template will not be bound to linkage problems. We present three implementations of this template: first, as a pure algorithm for search and optimization, second, as an artificial immune system, and third, as an algorithm for classifier rule base evolution, and compare implementation results and feature lists with similar algorithms. © 2008 Springer-Verlag Berlin Heidelberg
  6. Keywords:
  7. Genetic Algorithm ; ntrusion Detection ; Artificial Immune System ; Bayesian Optimization Algorithm ; Average Classification Rate
  8. Source: Studies in Computational Intelligence ; Volume 157 , 2008 , Pages 285-314 ; 1860949X (ISSN) ; 9783540850670 (ISBN)
  9. URL: https://link.springer.com/chapter/10.1007/978-3-540-85068-7_12