Special Topics in Intelligent Optimization Algorithm and Application
|
App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 6
1656-1662

Improved equilibrium optimizer based on adaptive crossover and covariance learning

Hou Xinyu1
Lu Haiyan1,2
Lu Mengdie1
Hu Qingyuan1
1. School of Science, Jiangnan University, Wuxi Jiangsu 214122, China
2. Wuxi Engineering Technology Research Center for Biological Computing, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0518

Abstract

Aiming at the problems of low convergence accuracy and ease of trapping into local stagnation in the equilibrium optimizer, this paper proposed an improved equilibrium optimizer based on adaptive crossover and covariance learning. Firstly, this algorithm constructed an external archive to retain the historically dominant individuals and increase the population diversity for improving the global optimization ability. Secondly, it introduced an adaptive crossover probability to balance the global exploration ability and local exploitation ability of the algorithm, so as to improve the optimization accuracy and robustness of the algorithm. Finally, it applied a covariance learning strategy to make full use of the relationship between the concentration vectors to enhance the information exchange among the populations and thereby to avoid local stagnation. Through simulation experiments on the CEC2019 test functions and combining the improved algorithm with back propagation(BP) neural network to predict the runoff situation of the Manas River in Xinjiang, the experimental results show that the improved algorithm remarkably improves convergence accuracy and robustness, and significantly enhances the runoff prediction performance of the BP neural network.

Foundation Support

国家自然科学基金资助项目(12102146)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0518
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 6
Section: Special Topics in Intelligent Optimization Algorithm and Application
Pages: 1656-1662
Serial Number: 1001-3695(2024)06-008-1656-07

Publish History

[2024-01-15] Accepted Paper
[2024-06-05] Printed Article

Cite This Article

侯新宇, 鲁海燕, 卢梦蝶, 等. 基于自适应交叉与协方差学习的改进平衡优化器算法 [J]. 计算机应用研究, 2024, 41 (6): 1656-1662. (Hou Xinyu, Lu Haiyan, Lu Mengdie, et al. Improved equilibrium optimizer based on adaptive crossover and covariance learning [J]. Application Research of Computers, 2024, 41 (6): 1656-1662. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)