Memetic Beluga Whale Optimization for Feature Selection

Jinrui Gao, Ziqian Wang, Baohang Zhang, Zhenyu Lei, Yuki Todo, Shangce Gao*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

With the increase in the dimensionality of data, feature selection has gained significant attention in recent times. Feature selection is a complex task due to the large search space involved. Swarm intelligence has recently been successfully used to address feature selection problems because of its global search ability. However, Beluga Whale Optimization (BWO), a swarm intelligence algorithm, is seldom used for feature selection due to its limited exploration ability at the end of iterations. Therefore, this paper proposes a new method called Memetic Beluga Whale Optimization (MBWO). By adding local perturbation and modifying search operators, MBWO can result in better performance in feature selection. Experiments comparing MBWO with other algorithms also show that the efficiency of the MBWO algorithm has significantly improved by these modifications.

Original languageEnglish
Title of host publicationProceedings - 2023 15th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9798350326178
DOIs
StatePublished - 2023
Event15th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2023 - Hangzhou, China
Duration: 2023/08/262023/08/27

Publication series

NameProceedings - 2023 15th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2023

Conference

Conference15th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2023
Country/TerritoryChina
CityHangzhou
Period2023/08/262023/08/27

Keywords

  • Beluga Whale Optimization
  • Classification
  • Feature selection

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Optimization

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