Q-learning improved golden jackal optimization algorithm and its application to reliability optimization of hydraulic system

Abstract To endow the prey with intelligent movement behavior and improve the performance of Golden Jackal Optimization (GJO), a Q-learning Improved Gold Jackal Optimization (QIGJO) algorithm is proposed. This paper introduces five update mechanisms and proposes double-population Q-learning collabor...

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Dongning Chen, Haowen Wang, Dongbo Hu, Qinggui Xian, Bingyu Wu
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Subjects:
Golden jackal optimization
Reliability optimization
Q-Learning
Global optimization
Online Access:https://doi.org/10.1038/s41598-024-75374-5

Internet

https://doi.org/10.1038/s41598-024-75374-5

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