Adaptive particle swarm optimization

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 39, Issue 6, 2009, Pages 1362-1381

  Zhan, Z H ^a   Zhang, J ^a   Li, Y ^b,c   Chung, H S H ^d  

^a SUN YAT SEN UNIVERSITY   (China)

^b UNIVERSITY OF GLASGOW   (United Kingdom)

^c UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^d CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Adaptive particle swarm optimization (APSO); Convergence; Evolutionary computation; Global optimization; Particle swarm optimization; Particle swarm optimization (PSO); State estimation

Indexed keywords

ACCELERATION COEFFICIENTS; ADAPTIVE PARTICLE SWARM OPTIMIZATION (APSO); ADAPTIVE PARTICLE SWARM OPTIMIZATIONS; ALGORITHM RELIABILITY; ALGORITHMIC PARAMETERS; AUTOMATIC CONTROL; CLASSICAL PARTICLE; CONVERGENCE; CONVERGENCE SPEED; ENTIRE SEARCHES; EVOLUTIONARY COMPUTATION; FASTER CONVERGENCE; GLOBAL OPTIMALITY; GLOBAL SEARCH; IMPLEMENTATION COMPLEXITY; INERTIA WEIGHT; LEARNING STRATEGY; LOCAL OPTIMA; MULTIMODAL BENCHMARK; NEW PARAMETERS; PARAMETER ADAPTATION; POPULATION DISTRIBUTION; RUNTIMES; SEARCH EFFICIENCY; SOLUTION ACCURACY; UNIMODAL;

AUTOMATION; COMPUTATIONAL EFFICIENCY; CONTROL; CONVERGENCE OF NUMERICAL METHODS; ESTIMATION; GLOBAL OPTIMIZATION; MAXIMUM LIKELIHOOD ESTIMATION; STATE ESTIMATION;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 70349626031     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2009.2015956     Document Type: Article

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