A comprehensive study of cuckoo-inspired algorithms

被引：51

作者：

Abdel-Basset, Mohamed ^{[1
]}

Hessin, Abdel-Naser ^{[1
]}

Abdel-Fatah, Lila ^{[1
]}

机构：

[1] Zagazig Univ, Fac Comp & Informat, Zagazig, Egypt

来源：

NEURAL COMPUTING & APPLICATIONS | 2018年 / 29卷 / 02期

关键词：

Metaheuristic; Cuckoo search; Cuckoo optimization algorithm; SEARCH ALGORITHM; OPTIMIZATION ALGORITHM; PARAMETER OPTIMIZATION; IMAGE SEGMENTATION; NEURAL-NETWORKS; COMBINED HEAT; DESIGN; CONTROLLER; SYSTEMS; DRIVEN;

D O I：

10.1007/s00521-016-2464-8

中图分类号：

TP18 [人工智能理论];

学科分类号：

140502 [人工智能];

摘要：

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.

引用

页码：345 / 361

页数：17

共 114 条

[1]

Cuckoo Search algorithm based load frequency controller design for nonlinear interconnected power system [J].