Earticle

초록

영어

Aiming at the drawback of the local search ability of weakness of adaptive chaos particle swarm optimization (ACPSO), which is based on the variance of population’s fitness, this paper presents that introduces the chaos mutation and chaos search to the ACPSO. By using the An chaos mapping to proceed the chaos mutation for some particles and take chaos search for the global optimal particle, it proposes a rule which takes into account the positions of particles and adaptive mutative scale of optimizing space. The results of numerical simulation show that the convergence, and the global and local search ability of the new method are improved, and can effectively avoid premature convergence.

목차

Abstract
 1. Introduction
 2. An Chaos Mapping
 3. The Modified PSO
  3.1. Standard PSO
  3.2. Initial Population Produced by Chaos Mapping
  3.3. Improvement of the Iterative Update
  3.4. Terminal Condition of Iteration
  3.5. The Entire Process of the Improved PSO
 4. Numerical Simulation
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Li Mengxia [ School of Information and Mathematics, Yangtze University, Jingzhou Hubei 434023, China and Petroleum Engineering College, Yangtze University, Jingzhou Hubei 434023, China and The Branch of Key Laboratory of CNPC for Oil and Gas Production, Yangtze University, Jingzhou Hubei 434023, China ]
• Liao Ruiquan [ The Branch of Key Laboratory of CNPC for Oil and Gas Production, Yangtze University, Jingzhou Hubei 434023, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605