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The Analysis of Hybrid Brain Storm Optimisation Approaches in Feature Selection

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Hybrid Artificial Intelligent Systems (HAIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14001))

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Abstract

The volume of data available has risen significantly in recent years due to advancements in data gathering techniques in different fields. The collected data in many domains are typically of high dimensionality, making it impossible to select an optimum range of features. There are many existing research papers that discuss feature selection process used by metaheuristic algorithm. One of them is brain storm optimisation (BSO) algorithm, which is relatively new swarm intelligence algorithm that mimics the brainstorming process in which a group of people solve a problem together. The aim of this paper is to present and analyse hybrid BSO algorithm solutions combined with other metaheuristic algorithms in feature selection process. The hybrid BSO algorithm overcomes the lack of exploitation in the original BSO algorithm; and simultaneously, the obtained statistical results prove the efficiency and robustness over other state-of-the-art approaches.

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Author information

Authors and Affiliations

  1. Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovića 6, 21000, Novi Sad, Serbia

    Dragan Simić & Svetislav D. Simić

  2. Frontiers Media SA, Paseo de Castellana 77, Madrid, Spain

    Zorana Banković

  3. University of Oviedo, Campus de Llamaquique, 33005, Oviedo, Spain

    José R. Villar

  4. Department of Industrial Engineering, University of A Coruña, 15405, Ferrol-A Coruña, Spain

    José Luis Calvo-Rolle

  5. Faculty of Medicine, University of Novi Sad, Hajduk Veljkova 1–9, 21000, Novi Sad, Serbia

    Svetlana Simić

Authors
  1. Dragan Simić
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  2. Zorana Banković
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  3. José R. Villar
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  4. José Luis Calvo-Rolle
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  5. Svetislav D. Simić
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  6. Svetlana Simić
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Corresponding author

Correspondence to Dragan Simić .

Editor information

Editors and Affiliations

  1. University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of Leon, León, Spain

    Hilde Pérez García

  3. University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  4. Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. University of Burgos, Burgos, Spain

    Álvaro Herrero

  7. University of A Coruña, Ferrol - Coruña, Spain

    José Luis Calvo Rolle

  8. University of A Coruña, Ferrol - Coruña, Spain

    Héctor Quintián

  9. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Simić, D., Banković, Z., Villar, J.R., Calvo-Rolle, J.L., Simić, S.D., Simić, S. (2023). The Analysis of Hybrid Brain Storm Optimisation Approaches in Feature Selection. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_40

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  • DOI: https://doi.org/10.1007/978-3-031-40725-3_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-40724-6

  • Online ISBN: 978-3-031-40725-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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