Study on inertia weight decreasing strategy of particle swarm optimization based on inverse coseca

The standard particle swarm optimization (pso), which introduces inertia weight w, is an effective method to find the extreme value of the function. However, particle swarm optimization (pso) has some disadvantages. When dealing with optimization problems, pso lacks effective parameter control and i...

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Vydané v:	Journal of physics. Conference series Ročník 1486; číslo 7; s. 72004 - 72009
Hlavní autori:	Liu, Huiming, Liu, Yong, Zhen, Jiaqi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bristol IOP Publishing 01.04.2020
Predmet:	Algorithms Convergence Extreme values Inertia Local optimization Machine learning Optimization Particle swarm optimization Physics Probability distribution functions Random numbers Weight
ISSN:	1742-6588, 1742-6596
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