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

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Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Studies in Computational Intelligence ; 828 | Springer eBooks Intelligent Technologies and RoboticsPublisher: Singapore : Springer, 2019Description: 1 Online-Ressource (X, 303 p. 155 illus., 69 illus. in color)ISBN:

9789811365690

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Additional physical formats: 9789811365683 | Erscheint auch als: 978-981-13-6568-3 Druck-AusgabeLOC classification:

Q342

DOI: DOI: 10.1007/978-981-13-6569-0Online resources:

Summary: 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 SystemsSummary: 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 fieldsPPN: PPN: 1666749133Package identifier: Produktsigel: ZDB-2-INR | ZDB-2-SEB | ZDB-2-SXIT

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