ISBN: 9781032770871 - nature-inspired metaheuristic algorithms: solving real world engineering problems (14 risultati)

hardcover. Condizione: Fine.

hardcover. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Hardback. Condizione: New. This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities.This book:Discusses load balancing and demand response using nature-inspired optimization techniquesPresents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithmsCovers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniquesExplains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniquesIllustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniquesNature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.…

Hardcover. Condizione: Brand New. 488 pages. 9.18x6.12x9.45 inches. In Stock.

Hardback. Condizione: New. This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities.This book:Discusses load balancing and demand response using nature-inspired optimization techniquesPresents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithmsCovers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniquesExplains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniquesIllustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniquesNature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.…

HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Sulabh Bansal received the BE in Computer Science and Engineering from Shivaji University Kolhapur in 2000, and M.Tech and PhD degrees from Dayalbagh Educational Institute, Agra in the year 2012 and 2017 respectively. He is a senior member of IEEE, a mem.…

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The text provides practical guidance to implement nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature-inspired metaheuristic algorithms have the potential to contribute to multiple UN SDG such as climate action, clean energy, and sustainable cities.…