Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 11
3271-3275

Whale optimization algorithm based on Gauss map and small hole imaging learning strategy

Xu Hang
Zhang Damin
Wang Yirou
Song Tingting
Wang Liqiao
College of Big Data & Information Engineering, Guizhou University, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2019.08.0282

Abstract

Aiming at the defects that the whale optimization algorithm(WOA) is easy to fall into the local optimal solution and the convergence speed is slow, this paper proposed a whale algorithm based on the small hole imaging reverse learning strategy to solve the defects. Firstly, this paper introduced the chaotic sequence generated by Gauss map to replace the original algorithm for increasing the diversity of the population. Secondly, it introduced a small hole imaging reverse learning strategy, on this basis, by combining with the optimal worst reverse learning method, which increased the diversity of the optimal position and improved the ability to jump out of local optimum. Finally, it added a nonlinear convergence factor and a logarithmic probability threshold in the algorithm to balance the exploration and exploitation of the algorithm while preserving the advantages of the whale algorithm. Through the simulation test of 10 benchmark functions, the experimental results show that the improved algorithm has obvious improvement in convergence speed and convergence precision performance.

Foundation Support

贵州省自然科学基金资助项目(黔科合基础[2017]1047号)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.08.0282
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 11
Section: Algorithm Research & Explore
Pages: 3271-3275
Serial Number: 1001-3695(2020)11-014-3271-05

Publish History

[2020-11-05] Printed Article

Cite This Article

徐航, 张达敏, 王依柔, 等. 基于高斯映射和小孔成像学习策略的鲸鱼优化算法 [J]. 计算机应用研究, 2020, 37 (11): 3271-3275. (Xu Hang, Zhang Damin, Wang Yirou, et al. Whale optimization algorithm based on Gauss map and small hole imaging learning strategy [J]. Application Research of Computers, 2020, 37 (11): 3271-3275. )

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  • Application Research of Computers Monthly Journal
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    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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