Fractional Order Darwinian Particle Swarm Optimization : Applications and Evaluation of an Evolutionary Algorithm
Couceiro, Micael
Fractional Order Darwinian Particle Swarm Optimization : Applications and Evaluation of an Evolutionary Algorithm by Micael Couceiro, Pedram Ghamisi - Cham Springer International Publishing 2016 - 1 recurso en línea (X, 75 páginas) 27 ilustraciones, 24 ilustraciones en color - SpringerBriefs in Applied Sciences and Technology 2191-530X .
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.
9783319196350
Inteligencia artificial
Sistemas, Teoría de
Q337.3 / C683 2016
006.3
Fractional Order Darwinian Particle Swarm Optimization : Applications and Evaluation of an Evolutionary Algorithm by Micael Couceiro, Pedram Ghamisi - Cham Springer International Publishing 2016 - 1 recurso en línea (X, 75 páginas) 27 ilustraciones, 24 ilustraciones en color - SpringerBriefs in Applied Sciences and Technology 2191-530X .
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.
9783319196350
Inteligencia artificial
Sistemas, Teoría de
Q337.3 / C683 2016
006.3