Paper Title:
Application of SVM Based on Improved Quantum Particle Swarm Optimization in Bio-Mimetic Robotic Horse
  Abstract

Quantum principles is introduced in particle swarm optimization to optimize SVM, aiming that common optimization algorithms of SVM are easy to relapse into local extreme values and optimization result bad. Quantum particle swarm optimization can improve traverse property of particle, thus can overcome the limitation of local extreme values and optimize SVM well. Use the optimized SVM to control the motion of bio-mimetic robotic horse. And simulation results show that this algorithm can achieve the best control effect quickly and accurately.

  Info
Periodical
Advanced Materials Research (Volumes 204-210)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
306-309
DOI
10.4028/www.scientific.net/AMR.204-210.306
Citation
Y. Y. Ren, J. Bao, M. Sun, H. R. Wang, "Application of SVM Based on Improved Quantum Particle Swarm Optimization in Bio-Mimetic Robotic Horse", Advanced Materials Research, Vols. 204-210, pp. 306-309, 2011
Online since
February 2011
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