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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 2/2018

15.07.2016 | Review

A comprehensive study of cuckoo-inspired algorithms

verfasst von: Mohamed Abdel-Basset, Abdel-Naser Hessin, Lila Abdel-Fatah

Erschienen in: Neural Computing and Applications | Ausgabe 2/2018

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Abstract

Nature-inspired metaheuristic algorithms are considered as the most effective techniques for solving various optimization problems. This paper provides a briefly review of the key features of the cuckoo-inspired metaheuristics: cuckoo search (CS) and cuckoo optimization algorithm (COA). In addition, it discusses some of their important and emerging studies, investigates their applications in several fields, and finally clarifies the differences between both algorithms so as to remove confusion between them.
Vorheriger Artikel Rough set–BPSO model for predicting vitamin D deficiency in apparently healthy Kuwaiti women based on hair mineral analysis
Nächster Artikel Nonlinear mathematical modeling of seed spacing uniformity of a pneumatic planter using genetic programming and image processing

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Metadaten
Titel
A comprehensive study of cuckoo-inspired algorithms
verfasst von
Mohamed Abdel-Basset
Abdel-Naser Hessin
Lila Abdel-Fatah
Publikationsdatum
15.07.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 2/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2464-8

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