Updating technique for particle swarm optimization in nonlinear dynamic systems

Syahrulanuar Ngah, Zhu Hui, Takaaki Baba

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルICAART 2009 - Proceedings of the 1st International Conference on Agents and Artificial Intelligence
ページ462-468
ページ数7
出版ステータスPublished - 2009
イベント1st International Conference on Agents and Artificial Intelligence, ICAART 2009 - Porto
継続期間: 2009 1 192009 1 21

Other

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

ASJC Scopus subject areas

  • 人工知能
  • ソフトウェア

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