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Socio-cultural inspired metaheuristics

Kulkarni, Anand J.

Socio-cultural inspired metaheuristics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Socio-cultural inspired metaheuristicsedited by Anand J. Kulkarni ... [et al.].
other author:	Kulkarni, Anand J.
Published:	Singapore :Springer Singapore :2019.
Description:	x, 303 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Computational intelligence.
Online resource:	https://doi.org/10.1007/978-981-13-6569-0
ISBN:	9789811365690$q(electronic bk.)

Socio-cultural inspired metaheuristics
Socio-cultural inspired metaheuristics[electronic resource] /edited by Anand J. Kulkarni ... [et al.]. - Singapore :Springer Singapore :2019. - x, 303 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8281860-949X ;. - Studies in computational intelligence ;v. 216..

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.

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.

ISBN: 9789811365690$q(electronic bk.)

Standard No.: 10.1007/978-981-13-6569-0doiSubjects--Topical Terms:

210824
Computational intelligence.

LC Class. No.: Q342 / .S635 2019

Dewey Class. No.: 006.3

Socio-cultural inspired metaheuristics
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505 0 $a 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.
520 $a 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.
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