A multi-mechanism balanced advanced learning sparrow search algorithm for UAV path planning-Reference-Cited by-同舟云学术

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A multi-mechanism balanced advanced learning sparrow search algorithm for UAV path planning

Published:2024-03-05 Issue:5 Volume:27 Page:6623-6666
ISSN:1386-7857
Container-title:Cluster Computing
language:en
Short-container-title:Cluster Comput

Author:

Yang Chao,Yang Hong,Zhu Donglin,Hu YiWen,Zhang Yu,Ma HongYuan,Zhang Di

Funder

National Natural Science Foundation of China

Liaoning Revitalization Talents Program

Shenyang science and technology innovation talent support plan

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10586-024-04290-0.pdf

Reference54 articles.

1. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Icnn95-International Conference on Neural Networks, IEEE (1995). https://doi.org/10.1109/ICNN.1995.488968

2. Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperating agents. IEEE Trans. Syst. Man Cybern. Part B 26(1), 29–42 (1996). https://doi.org/10.1109/3477.484436

3. Goldberg, D.E., Holland, J.H.: Genetic algorithms and machine learning. Mach. Learn. 3, 95–99 (1988). https://doi.org/10.1023/A:1022602019183

4. Zhu, D., Wang, S., Shen, J., Zhou, C., Li, T., Yan, S.: A multi-strategy particle swarm algorithm with exponential noise and fitness-distance balance method for low-altitude penetration in secure space. J. Comput. Sci. 74, 102149 (2023). https://doi.org/10.1016/j.jocs.2023.102149

5. Zhu, D., Wang, S., Zhou, C., Yan, S., Xue, J.: Human memory optimization algorithm: a memory-inspired optimizer for global optimization problems. Expert Syst. Appl. 237, 121597 (2024). https://doi.org/10.1016/j.eswa.2023.121597

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