Updating technique for particle swarm optimization in nonlinear dynamic systems

Syahrulanuar Ngah, Zhu Hui, Takaaki Baba

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

Abstract

Dealing with searching and tracking an optimal solution in dynamic environment becomes more frequently nowadays. For dealing with this matter, Particle Swarm Optimization - Random Times Variable Inertia Weight and Acceleration Coefficient (PSO-RTVIWAC) concept, motivated by Particle Swarm Optimization-Time Variable Acceleration Coefficient (PSO-TVAC) and Particle Swarm Optimization-Random Inertia Weight (PSO-RANDIW) was introduced. PSO-RTVIWAC can accomplish an acceptable accuracy in detecting the target with the small number of particle and iteration. This paper will discuss about modifying the fitness value in the update mechanism for determining the local best and global best to improve the accuracy of detecting the target. By adding a constant value to the current stored fitness value, it will give the opportunity to the next fitness value to be the best fitness value. The result from this modifying technique then will be compared with PSO-RTVIWAC to evaluate the performance.

Original languageEnglish
Title of host publicationICAART 2009 - Proceedings of the 1st International Conference on Agents and Artificial Intelligence
Pages462-468
Number of pages7
Publication statusPublished - 2009
Event1st International Conference on Agents and Artificial Intelligence, ICAART 2009 - Porto
Duration: 2009 Jan 192009 Jan 21

Other

Other1st International Conference on Agents and Artificial Intelligence, ICAART 2009
CityPorto
Period09/1/1909/1/21

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Keywords

  • Fitness value
  • Nonlinear dynamic systems
  • Particle swarm

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Ngah, S., Hui, Z., & Baba, T. (2009). Updating technique for particle swarm optimization in nonlinear dynamic systems. In ICAART 2009 - Proceedings of the 1st International Conference on Agents and Artificial Intelligence (pp. 462-468)