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Fractional Order Darwinian Particle Swarm Optimization : Applications and Evaluation of an Evolutionary Algorithm / by Micael Couceiro, Pedram Ghamisi

By: Couceiro, Micael
Contributor(s): SpringerLink (Online service) | Ghamisi, Pedram
Material type: materialTypeLabelE-bookSeries: (SpringerBriefs in Applied Sciences and Technology, 2191-530X).Publisher: Cham : Springer International Publishing, 2016Description: 1 recurso en línea (X, 75 páginas) : 27 ilustraciones, 24 ilustraciones en color.ISBN: 9783319196350.Subject: Inteligencia artificial | Sistemas, Teoría deDDC classification: 006.3 Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Particle Swarm Optimization (PSO) -- Fractional Order Darwinian PSO (FODPSO) -- Case Study I: Curve Fitting -- Case Study II: Image Segmentation -- Case Study III: Swarm Robotics -- Conclusions.
Abstract: 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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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q337.3 C683 2016 EB (Browse shelf(Opens below)) .i11583824 Acceso electrónico eBOOK .i11583824
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Particle Swarm Optimization (PSO) -- Fractional Order Darwinian PSO (FODPSO) -- Case Study I: Curve Fitting -- Case Study II: Image Segmentation -- Case Study III: Swarm Robotics -- Conclusions.

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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