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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 488 pages. 9.18x6.12x9.45 inches. In Stock.
Language: English
Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 1032770872 ISBN 13: 9781032770871
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 1032770872 ISBN 13: 9781032770871
Seller: CitiRetail, Stevenage, United Kingdom
Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Add to basketHRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Condition: 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.
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Buch. Condition: 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.
Language: English
Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 1032770872 ISBN 13: 9781032770871
Seller: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.