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Applications of Cuckoo Search Algorithm and its Variants / / edited by Nilanjan Dey



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Titolo: Applications of Cuckoo Search Algorithm and its Variants / / edited by Nilanjan Dey Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021
Edizione: 1st ed. 2021.
Descrizione fisica: 1 online resource (328 pages)
Disciplina: 025.524
Soggetto topico: Computational intelligence
Algorithms
Mathematical optimization
Computational Intelligence
Algorithm Analysis and Problem Complexity
Continuous Optimization
Persona (resp. second.): DeyNilanjan
Nota di contenuto: Cuckoo Search Algorithm for Parametric Data Fitting of Characteristic Curves of the Van der Waals Equation of State -- Cuckoo search algorithm with various walks -- Cuckoo search algorithm: Statistical-based optimization approach and engineering applications -- Training a Feed Forward Neural Network using Cuckoo Search -- A Cuckoo Search Algorithm Inspired Membrane Systems to Solve Optimization Problems -- Cuckoo Search for Optimum Design of Real-Sized High-Level Steel Frames.
Sommario/riassunto: This book highlights the basic concepts of the CS algorithm and its variants, and their use in solving diverse optimization problems in medical and engineering applications. Evolutionary-based meta-heuristic approaches are increasingly being applied to solve complicated optimization problems in several real-world applications. One of the most successful optimization algorithms is the Cuckoo search (CS), which has become an active research area to solve N-dimensional and linear/nonlinear optimization problems using simple mathematical processes. CS has attracted the attention of various researchers, resulting in the emergence of numerous variants of the basic CS with enhanced performance since 2019.
Titolo autorizzato: Applications of Cuckoo Search Algorithm and its Variants  Visualizza cluster
ISBN: 981-15-5163-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910768467803321
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Serie: Springer Tracts in Nature-Inspired Computing, . 2524-552X