Art

J-GLOBAL ID：201802272341598499   Reference number：18A0360265

The Search Feature of Particle Swarm Optimizer with Sensors in Dynamic Environment

動的環境下でのセンサ付き粒子群オプティマイザの探索特徴

Author (1)： SHO HIROSHI (九州工大 大学院生命体工学研究科)
Material： 電子情報通信学会技術研究報告  (IEICE Technical Report (Institute of Electronics, Information and Communication Engineers))
Volume： 117  Issue： 417(NC2017 50-66)  Page： 77-82  Publication year： Jan. 19, 2018 
JST Material Number： S0532B  ISSN： 0913-5685  Document type： Proceedings
Article type： 原著論文  Country of issue： Japan (JPN)  Language： JAPANESE (JA)

Thesaurus term： Environment ,  *sensor ,  *optimization ,  artificial intelligence ,  performance ,  moving object ,  simulation ,  *particle swarm optimization ,  swarm intelligence ,  pursuit problem ,  *modification
Semi thesaurus term： *dynamic environment ,  search performance ,  moving target

JST classification (2)： Artificial intelligence  (JE08000Z) ,  Numerical computation  (JE02000J)

Reference (15)：

• T.M. Blackwell, ′′Swarms in dynamic environments,′′ Proceedings. of the 2003 Genetic and Evolutionary Computation Conference, LNCS, pp.1-12, 2003.
• M. Clerc and J. Kennedy, ′′The particle swarm-explosion, stability, and convergence in a multidimensional complex space,′′ IEEE Transactions on Evolutionary Computation, vol.6, no.1, pp.58-73, 2000.
• M. Clerc, Particle Swarm Optimization, Hermes Science Pubns, UK, 2006.
• X. Cui and T.E. Potok, ′′Distributed Adaptive Particle Swarm Optimizer in Dynamic Environment,′′ IEEE International Parallel and Distributed Processing Symposium, pp.1-7, Long Beach, CA, 26-30, Mar. 2007.
• R.C. Eberhart and Y. Shi, ′′Comparing inertia weights and constriction factors in particle swarm optimization,′′ Proceedings of the 2000 IEEE Congress on Evolutionary Computation, vol.1, pp.84-88, San Diego, CA, 2000.

Terms in the title (3)： 動的環境 ,  粒子群 ,  探索