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The GEPSO-Classification Algorithm

  • Weihong Wang
  • Dandan Jin
  • Qu Li
  • Zhaolin Fang
  • Jie Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8346)

Abstract

In order to solve the problem that the evolutionary algorithm based class center classification algorithm easily falls into a local optimum later in the process, this paper proposes a Gene Expression Programming(GEP) classification algorithm which is optimized by Particle Swarm Optimization(PSO). It’s named after the GEPSO-Classification Algorithm, and the word GEPSO comes from the combination of the word GEP and PSO. This algorithm first finds a suboptimal solution on the merit that GEP can converge rapidly in the early stage, then with this suboptimal solution, the algorithm searches the optimal solution on the merit that PSO is more likely to converge to the optimal solution. The experimental result shows that this algorithm has a better performance on classification.

Keywords

GEP PSO Classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Weihong Wang
    • 1
    • 2
  • Dandan Jin
    • 2
  • Qu Li
    • 2
  • Zhaolin Fang
    • 2
  • Jie Yang
    • 2
  1. 1.State Key Laboratory of Software Development EnvironmentBeihang UniversityBejingChina
  2. 2.College of Computer ScienceZhejiang University of TechnologyHangzhouChina

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