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Socio-cultural Inspired Metaheuristics [[electronic resource] /] / edited by Anand J. Kulkarni, Pramod Kumar Singh, Suresh Chandra Satapathy, Ali Husseinzadeh Kashan, Kang Tai



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Titolo: Socio-cultural Inspired Metaheuristics [[electronic resource] /] / edited by Anand J. Kulkarni, Pramod Kumar Singh, Suresh Chandra Satapathy, Ali Husseinzadeh Kashan, Kang Tai Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019
Edizione: 1st ed. 2019.
Descrizione fisica: 1 online resource (308 pages) : illustrations
Disciplina: 006.3
Soggetto topico: Computational intelligence
Artificial intelligence
Mathematical optimization
Computational Intelligence
Artificial Intelligence
Continuous Optimization
Persona (resp. second.): KulkarniAnand J
SinghPramod Kumar
SatapathySuresh Chandra
Husseinzadeh KashanAli
TaiKang
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Optimum Design of Four Mechanical Elements Using Cohort Intelligence Algorithm -- Premier League Championship Algorithm: a multi-population based Algorithm and its Application on Structural Design Optimization -- Socio-inspired Optimization Metaheuristics: A Review -- Social Group Optimization Algorithm for Pattern Optimization in Antenna Arrays -- A Self-organizing Multi-agent Cooperative Robotic System: An Application of Cohort Intelligence Algorithm -- Feature Selection for Vocal Segmentation Using Social Emotional Optimization Algorithm -- Simultaneous Size and Shape Optimization of Dome-shaped Structures Using Improved Cultural Algorithm -- A Socio-Based Cohort Intelligence Algorithm for Integer Discrete and Mixed Design Variables Engineering Problems -- Maximizing Profits in Crop Planning Using Socio Evolution and Learning Optimization -- Application of Cohort- intelligence Variations Designing Fractional PID Controller for Various Systems.
Sommario/riassunto: This book presents the latest insights and developments in the field of socio-cultural inspired algorithms. Akin to evolutionary and swarm-based optimization algorithms, socio-cultural algorithms belong to the category of metaheuristics (problem-independent computational methods) and are inspired by natural and social tendencies observed in humans by which they learn from one another through social interactions. This book is an interesting read for engineers, scientists, and students studying/working in the optimization, evolutionary computation, artificial intelligence (AI) and computational intelligence fields.
Titolo autorizzato: Socio-cultural Inspired Metaheuristics  Visualizza cluster
ISBN: 981-13-6569-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484748503321
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Serie: Studies in Computational Intelligence, . 1860-949X ; ; 828