A self-adaptive Harris Hawks optimization algorithm with opposition-based learning and chaotic local search strategy for global optimization and feature selection-Reference-Cited by-同舟云学术

A self-adaptive Harris Hawks optimization algorithm with opposition-based learning and chaotic local search strategy for global optimization and feature selection

Published:2021-04-16 Issue:2 Volume:13 Page:309-336
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Hussien Abdelazim G.^ORCID,Amin Mohamed

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/s13042-021-01326-4.pdf

Reference75 articles.

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3. Alabool HM, Alarabiat D, Abualigah L, Heidari AA (2021) Harris hawks optimization: a comprehensive review of recent variants and applications. Neural Comput Appl:1–42

4. Alatas B (2010) Chaotic bee colony algorithms for global numerical optimization. Expert Syst Appl 37(8):5682–5687

5. Antoniou A (2016) Digital signal processing. McGraw-Hill, New York

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