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Hierarchical learning particle swarm optimization using fuzzy logic., , и . Expert Syst. Appl., (декабря 2023)Hybrid bio-inspired user clustering for the generation of diversified recommendations., , , , и . Neural Comput. Appl., 32 (7): 2487-2506 (2020)Improving evolutionary algorithms with information feedback model for large-scale many-objective optimization., , и . Appl. Intell., 53 (10): 11439-11473 (мая 2023)Architecture evolution of convolutional neural network using monarch butterfly optimization., , и . J. Ambient Intell. Humaniz. Comput., 14 (9): 12257-12271 (2023)Enhancing MOEA/D with information feedback models for large-scale many-objective optimization., , , , , и . Inf. Sci., (2020)Comparison of Two Swarm Intelligence Algorithms: From the Viewpoint of Learning., , , , , и . ICIC (3), том 10956 из Lecture Notes in Computer Science, стр. 821-827. Springer, (2018)Solving IIR system identification by a variant of particle swarm optimization., , и . Neural Comput. Appl., 30 (3): 685-698 (2018)Improved elephant herding optimization using opposition-based learning and K-means clustering to solve numerical optimization problems., и . J. Ambient Intell. Humaniz. Comput., 14 (3): 1753-1784 (марта 2023)Monarch butterfly optimized control with robustness analysis for grid tied centralized and distributed power generations., , , , и . J. Ambient Intell. Humaniz. Comput., 13 (7): 3595-3608 (2022)Domination landscape in evolutionary algorithms and its applications., , , , и . Soft Comput., 23 (11): 3563-3570 (2019)