Optimization Algorithm of Spotted Hyena Based on Chaotic Reverse Learning Strategy
Authors: 
Xu He, Hengzhi Lu, Zixing LingAuthors Info & Claims
Xu He, Hengzhi Lu, Zixing LingAuthors Info & ClaimsPages 251 - 256
Abstract
The application of swarm optimization algorithm in WSNs has become a new research hotspot of scholars at home and abroad. Aiming at the problem that the spotted hyena optimization algorithm is easy to fall into local optimum, which leads to low optimization accuracy, an improved spotted hyena optimization algorithm is proposed. On the basis of the original algorithm, Sine chaotic map and elite reverse learning strategy are embedded to reduce the probability of falling into local optimum and improve the global search ability of spotted hyena optimization algorithm. In addition, the adaptive inertia weight is introduced to balance the global search and local development capabilities of the spotted hyena optimization algorithm. The experimental results show that compared with the original spotted hyena optimization algorithm, sine and cosine algorithm, multiverse optimization algorithm, differential evolution algorithm and particle swarm optimization algorithm, the improved algorithm has significant performance advantages in optimization ability and stability.
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Index Terms
- Optimization Algorithm of Spotted Hyena Based on Chaotic Reverse Learning Strategy
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Published In
September 2022
1221 pages
ISBN:9781450396899
DOI:10.1145/3573942
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Published: 16 May 2023
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AIPR 2022
AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition
September 23 - 25, 2022
Xiamen, China
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