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Fractional Order Darwinian Particle Swarm Optimization

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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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Detail Information

Series Title

SpringerBriefs in Applied Sciences and Technology

Call Number

-

Publisher

Cham : Springer., 2015

Collation

X, 75 pages

Language

English

ISBN/ISSN

978-3-319-19635-0

Classification

NONE

Content Type

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Media Type

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Carrier Type

-

Edition

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Subject(s)

Computational Intelligence

Specific Detail Info

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Statement of Responsibility

Micael Couceiro , Pedram Ghamisi

Other Information

Cataloger

Jemadi

Source

-

Validator

Jemadi

Digital Object Identifier (DOI)

https://doi.org/10.1007/978-3-319-19635-0

Journal Volume

-

Journal Issue

-

Subtitle

Applications and Evaluation of an Evolutionary Algorithm

Parallel Title

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