Nature-Inspired Optimizers
Theories, Literature Reviews and Applications
Buch in deiner Nähe kaufen
Beschreibung
This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.
This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.
Offers a comprehensive tutorial on evolutionary optimization Describes the mathematical model each algorithm is based on Reports on several benchmark case studies Source codes are available on a dedicated webpage
Autor*in
Seyedali Mirjalili
Themen in »Nature-Inspired Optimizers«
Ant Colony Optimizer AUV Path Planning Continuous Ant Colony Ant Lion Optimizer Dragonfly Algorithm Feature Selection Continuous Genetic Algorithm Image Reconstruction Controlling Parameter of Genetic Algorithm Controlling Parameter of Grey Wolf Optimizer Whale Optimization Algorithm Sine Cosine Algorithm Swarm Algorithm in Extreme Learning Machine Local Optima Stagnation Optimized Controllers