Evolutionary and Swarm Intelligence Algorithms

Jagdish Chand Bansal

ISBN 10: 3030082296 / ISBN 13: 9783030082291

Editore: Springer International Publishing, Springer Nature Switzerland, 2019

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.

Codice articolo 9783030082291

Dati bibliografici

• Titolo: Evolutionary and Swarm Intelligence Algorithms
• Editore: Springer International Publishing, Springer Nature Switzerland
• Data di pubblicazione: 2019
• Lingua: Inglese
• ISBN 10: 3030082296
• ISBN 13: 9783030082291
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 12 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 12 millimetri di profondità
• Peso: 312 grammi

Descrizione articolo

Riassunto

Dalla quarta di copertina

This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.