Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
729-735

Improved beluga whale optimization algorithm based on chaotic inverse learning and water wave algorithm

Wang Yahui
Zhang Huchen
Wang Xuebing
Hu Jiming
Li Ya
College of Mechanical, North China University of Water Resources & Electric Power, Zhengzhou 450045, China
DOI: 10.19734/j.issn.1001-3695.2023.07.0332

Abstract

To address the problems of the original BWO algorithm, such as insufficient exploration and exploitation ability in the middle and late stages in some cases, reduce the diversity and solution accuracy, easy to fall into local optimality, this paper proposed a white whale optimization algorithm(TWBWO) based on chaotic backward learning and water wave algorithm improvement. Further it improved the computational accuracy and convergence speed of Moby Dick algorithm, enhanced the ability of global search and jumping out of local optimum. Combining chaotic mapping and backward learning strategies, it improved the quality and diversity of populations and speeded up the convergence rate. It introduced the refraction operation of the WWO to avoid the algorithm from repeatedly falling into local optima and improve the computational accuracy. The experimental results show that the TWBWO algorithm is superior to the original algorithm and other classical algorithms in terms of convergence speed and solution accuracy as well as stability, with better performance and better finding ability.

Foundation Support

河南省科技攻关项目(212102210051)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.07.0332
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: Algorithm Research & Explore
Pages: 729-735
Serial Number: 1001-3695(2024)03-013-0729-07

Publish History

[2023-10-12] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

王亚辉, 张虎晨, 王学兵, 等. 基于混沌反向学习和水波算法改进的白鲸优化算法 [J]. 计算机应用研究, 2024, 41 (3): 729-735. (Wang Yahui, Zhang Huchen, Wang Xuebing, et al. Improved beluga whale optimization algorithm based on chaotic inverse learning and water wave algorithm [J]. Application Research of Computers, 2024, 41 (3): 729-735. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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