An improved multi-population whale optimization algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s13042-022-01537-3.pdf
Reference67 articles.
1. Abderazek H, Hamza F, Yildiz AR, Sait SM (2021) Comparative investigation of the moth-flame algorithm and whale optimization algorithm for optimal spur gear design. Mater Test 63(3):266–271
2. Agarwal P, Mehta S, Abraham A (2021) A meta-heuristic density-based subspace clustering algorithm for high-dimensional data. Soft Comput 25(15):10237–10256
3. Asghari K, Masdari M, Gharehchopogh FS, Saneifard R (2021) Multi-swarm and chaotic whale-particle swarm optimization algorithm with a selection method based on roulette wheel. Expert Syst 38(8):e12779
4. Ashraf NM, Mostafa RR, Sakr RH, Rashad M (2021) Optimizing hyperparameters of deep reinforcement learning for autonomous driving based on whale optimization algorithm. Plos One 16(6):e0252754
5. Askarzadeh A (2016) A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Comput Struct 169:1–12
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