Sensitivity analysis on Gaussian quantum-behaved particle swarm optimization control parameters

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that falls under the category of nature-inspired algorithms and is similar to evolutionary computing in various ways. Rather than the survival of the fittest, the PSO is driven by a representation of a social psycho...

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Vydané v:	Soft computing (Berlin, Germany) Ročník 27; číslo 13; s. 8759 - 8774
Hlavní autori:	Rugveth, Vankayala Sai, Khatter, Kiran
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2023
Predmet:	Artificial Intelligence Computational Intelligence Control Engineering Mathematical Logic and Foundations Mechatronics Optimization Robotics Sensitive analysis Optimal parameter set Particle swarm optimization (PSO) Quantum-behaved particle swarm optimization (QPSO) Gaussian quantum-behaved particle swarm optimization-optimal parameter set (GQPSO-OPS) Constrained optimization Control parameters
ISSN:	1432-7643, 1433-7479
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