A particle swarm optimizer with multi-level population sampling and dynamic p-learning mechanisms for large-scale optimization Article Swipe

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Mengmeng Sheng , Zidong Wang , Weibo Liu , Xi Wang , Shengyong Chen , Xiaohui Liu ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.1016/j.knosys.2022.108382

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Particle Swarm Optimization

Benchmark (Surveying)

Computer Science

Swarm Behaviour

Evolutionary Algorithm

Artificial Intelligence

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Particle swarm optimization Benchmark (surveying) Computer science Swarm behaviour Mathematical optimization Multi-swarm optimization Population Scale (ratio) Mechanism (biology) Sampling (signal processing) Evolutionary algorithm Metaheuristic Swarm intelligence Artificial intelligence Mathematics Machine learning Physics Sociology Geography Quantum mechanics Demography Geodesy Computer vision Filter (signal processing)

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Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.knosys.2022.108382
OA Status: green
Cited By: 27
References: 44
Related Works: 10
OpenAlex ID: https://openalex.org/W4211082065

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DOI: https://doi.org/10.1016/j.knosys.2022.108382

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Title: A particle swarm optimizer with multi-level population sampling and dynamic p-learning mechanisms for large-scale optimization

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Type: article

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Language: en

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Publication year: 2022

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Publication date: 2022-02-12

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Authors: Mengmeng Sheng, Zidong Wang, Weibo Liu, Xi Wang, Shengyong Chen, Xiaohui Liu

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Landing page: https://doi.org/10.1016/j.knosys.2022.108382

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Concepts: Particle swarm optimization, Benchmark (surveying), Computer science, Swarm behaviour, Mathematical optimization, Multi-swarm optimization, Population, Scale (ratio), Mechanism (biology), Sampling (signal processing), Evolutionary algorithm, Metaheuristic, Swarm intelligence, Artificial intelligence, Mathematics, Machine learning, Physics, Sociology, Geography, Quantum mechanics, Demography, Geodesy, Computer vision, Filter (signal processing)

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Cited by: 27

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Citations by year (recent): 2025: 4, 2024: 8, 2023: 11, 2022: 4

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References (count): 44

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Related works (count): 10

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