ENGLISH

Fractional Order Darwinian Particle Swarm Optimization: Applications and Evaluation of an Evolutionary Algorithm

By Micael Couceiro , Pedram Ghamisi (auth.)

Book information

Publisher
Springer International Publishing
Year
2016
ISBN
978-3-319-19634-3, 978-3-319-19635-0
DOI
10.1007/978-3-319-19635-0
Language
english
Format
PDF
Filesize
5 MB (5263314 bytes)
Series
SpringerBriefs in Applied Sciences and Technology
Edition
1
Pages
75\82
Time added
2015-07-18 18:00:00
Computational Intelligence; Artificial IntelligencControl

Description

This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, such as its ability to provide an improved convergence towards a solution, while avoiding sub-optimality. This book offers a valuable resource for researchers in the fields of robotics, sports science, pattern recognition and machine learning, as well as for students of electrical engineering and computer science.

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