Socio-cultural inspired metaheuristics
- Responsibility
- Anand J. Kulkarni, Pramod Kumar Singh, Suresh Chandra Satapathy, Ali Husseinzadeh Kashan, Kang Tai, editors.
- Digital
- text file
- Publication
- Singapore : Springer, 2019.
- Physical description
- 1 online resource (x, 303 pages) : illustrations (some color)
- Series
- Studies in computational intelligence ; v. 828. 1860-949X
Online
Available online
More options
Description
Creators/Contributors
- Contributor
- Kulkarni, Anand Jayant, editor.
- Singh, Pramod Kumar, editor.
- Satapathy, Suresh Chandra, 1964- editor.
- Kashan, Ali Husseinzadeh, editor.
- Tai, Kang, editor.
Contents/Summary
- Contents
-
- 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.
- (source: Nielsen Book Data)
- Publisher's summary
-
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.
(source: Nielsen Book Data)
Subjects
Bibliographic information
- Publication date
- 2019
- Series
- Studies in Computational Intelligence, 1860-949X ; volume 828
- Note
- Includes author index.
- ISBN
- 9789811365690 (electronic bk.)
- 9811365695 (electronic bk.)
- 9789811365706 (print)
- 9811365709
- 9789811365713 (print)
- 9811365717
- 9789811365683 (print)
- 9811365687
- DOI
- 10.1007/978-981-13-6569-0
