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Research on Hierarchical Mechanism of Strictly Metric-Free Model Modeling and Parameter Optimization

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Proceedings of 2023 Chinese Intelligent Systems Conference (CISC 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1091))

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Abstract

Swarm phenomena are ubiquitous in the biological world. Researching swarm models can provide us with many biological insights, hel** to reveal the behavioral mechanisms behind groups of birds, fish, insects, and mammals, and providing many solutions for cooperative control in multi-agent systems. In the study of swarm models, it is often assumed that information exchange between model individuals is equal, but many researchers have found that rank mechanisms between leaders and followers are widespread in biological populations. Therefore, based on the leader mechanism in the Couzin model, this paper proposes a strictly metric-free model with a rank mechanism and optimizes swarm model parameters using the differential evolution algorithm to explore the impact of rank mechanisms on swarm efficiency. Through numerous numerical simulation experiments, we found that the smaller the population size, the larger the required preference direction weight \(\omega \), and the larger the population size, the smaller the required preference direction weight \(\omega \). After comparing the optimized model with the unoptimized model through quantitative analysis, the optimized model showed higher consistency after the system reached stability, proving the effectiveness of the differential evolution algorithm in optimizing swarm model parameters.

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Authors and Affiliations

  1. University of Science and Technology Bei**g, Bei**g, China

    Qing Li, Weilin Zhang, Yongnan Jia, Yaming **, Yuxuan Lin & Weicun Zhang

Authors
  1. Qing Li
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  2. Weilin Zhang
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  3. Yongnan Jia
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  4. Yaming **
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  5. Yuxuan Lin
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  6. Weicun Zhang
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Corresponding author

Correspondence to Yongnan Jia .

Editor information

Editors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Bei**g, China

    Yingmin Jia

  2. School of Automation and Electrical Engineering, University of Science and Technology Bei**g, Bei**g, China

    Weicun Zhang

  3. School of Mechanical Engineering and Automation, Beihang University, Bei**g, China

    Yongling Fu

  4. Ningbo Institute of Materials Technology&Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang, China

    Jiqiang Wang

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Li, Q., Zhang, W., Jia, Y., **, Y., Lin, Y., Zhang, W. (2023). Research on Hierarchical Mechanism of Strictly Metric-Free Model Modeling and Parameter Optimization. In: Jia, Y., Zhang, W., Fu, Y., Wang, J. (eds) Proceedings of 2023 Chinese Intelligent Systems Conference. CISC 2023. Lecture Notes in Electrical Engineering, vol 1091. Springer, Singapore. https://doi.org/10.1007/978-981-99-6886-2_1

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