Fractional Order Darwinian Particle Swarm Optimization
Applications and Evaluation of an Evolutionary Algorithm
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Beschreibung
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.
Contributes to the state-of-the-art on the use of swarm intelligence to solve real-world problems Compares the capabilities of various bio-inspired optimization approaches Demonstrates the superiority of the Fractional Order Darwinian Particle Swarm Optimization (FODPSO) algorithm Includes supplementary material: sn.pub/extras
Autor*in
Micael Couceiro
Themen in »Fractional Order Darwinian Particle Swarm Optimization«
Advantages of FODPSO Bio-inspired optimization approaches Bottom-up applicability of swarm intelligence Curve fitting PSO DPSO Discrete Particle Swarm Optimization FODPSO FODPSO real-world problems Fractional Order Darwinian Particle Swarm Optimization Image segmentation PSO PSO Particle Swarm Optimization Superiority of FODPSO Swarm robotics PSO