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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Veröffentlicht in:	Journal of physics. Conference series Jg. 1486; H. 7; S. 72004 - 72009
Hauptverfasser:	Liu, Huiming, Liu, Yong, Zhen, Jiaqi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bristol IOP Publishing 01.04.2020
Schlagworte:	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
Online-Zugang:	Volltext
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