Chaotic map enabled algorithm hybridizing Hunger Games Search algorithm with Aquila Optimizer
Konferenz: ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application
17.12.2021 - 19.12.2021 in Shenyang, China
Tagungsband: ICMLCA 2021
Seiten: 5Sprache: EnglischTyp: PDF
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Autoren:
Zhang, Yujun; Zhao, Juan (School of Electronics and Information Engineering, Jingchu University of Technology, Jing men, China)
Yan, Yuxin (Academy of Arts, Jingchu University of Technology, Jing men, China)
Gao, Zhengming (School of Computer Engineering, Jingchu University of Technology & Institute of Intelligent Information Technology, Jingmen Industrial Technology Research Institute, Jing men, China)
Inhalt:
In the improvement of the algorithm, the performance of the algorithm is usually improved by introducing mapping, mixing other algorithms, etc. Due to the characteristics of chaotic mapping, the randomness of the algorithm can be improved, and the hybrid algorithm can combine the advantages of two or more algorithms to improve the performance of the algorithm. In this paper, the multiplicative mapping is introduced. It first improves the performance of the algorithm, and then mixes the multiplicative map enabled Hunger Games Search (HGS) algorithm with the Aquila Optimizer (AO) algorithm, and it is called CHGSAO in this paper. Because the search performance of the HGS algorithm is weak, but the AO search performance is strong, the advantages of the AO algorithm are used to make up the defects of the multiplicative map enabled HGS algorithm. The results show that this improvement is effective and can significantly improve the performance of the algorithm.