Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 7
2068-2074

Salp swarm algorithm based on adaptive t-distribution and dynamic weight

Hu Jingjie
Chu Zhaobi
Guo Yule
Dong Xueping
Zhu Min
School of Electrical Engineering & Automation, Hefei University of Technology, Hefei 230009, China
DOI: 10.19734/j.issn.1001-3695.2022.11.0628

Abstract

Aiming at the shortcoming of salp swarm optimization algorithm such as low accuracy, slow convergence speed and easy to fall into local optimum, this paper proposed an adaptive t-distribution and dynamic weight salp swarm optimization algorithm. Firstly, the leader position update introduced the global search stage formula of butterfly optimization algorithm to enhance the global exploration ability. Secondly, the follower location update introduced an adaptive dynamic weighting factor to strengthen the guiding role of elite individuals, so as to enhance the local development ability. Finally, the adaptive t-distribution mutation strategy mutated the optimal individual in order to avoid the algorithm falling into local optimum. By solving 12 benchmark test functions, and according to comparison results of the mean value, standard deviation, solving success rate, Wilcoxon test and convergence curve, the proposed algorithm was superior to standard salp swarm algorithm, the compared other improved salp swarm algorithm and the compared other swarm intelligence algorithms. The results also show that it has a significant improvement in the optimization accuracy and convergence speed, and has the ability to jump out of local optimum. The experimental results verify the effectiveness of the proposed algorithm by applying it to find the lowest point of denitrification inlet concentration.

Foundation Support

安徽省科技重大专项项目(202103a05020001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.11.0628
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 7
Section: Algorithm Research & Explore
Pages: 2068-2074
Serial Number: 1001-3695(2023)07-022-2068-07

Publish History

[2023-01-31] Accepted Paper
[2023-07-05] Printed Article

Cite This Article

胡竞杰, 储昭碧, 郭愉乐, 等. 基于自适应t分布与动态权重的樽海鞘群算法 [J]. 计算机应用研究, 2023, 40 (7): 2068-2074. (Hu Jingjie, Chu Zhaobi, Guo Yule, et al. Salp swarm algorithm based on adaptive t-distribution and dynamic weight [J]. Application Research of Computers, 2023, 40 (7): 2068-2074. )

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.

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