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Mathematical Foundations Nature Inspired Algorithms by Yang Xin She (16 results)
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Mathematical Foundations of Nature-inspired Algorithms
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Mathematical Foundations of Nature-Inspired Algorithms (SpringerBriefs in Optimization)
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Mathematical Foundations of Nature-inspired Algorithms
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Paperback. Condition: Brand New. 120 pages. 9.25x6.10x0.28 inches. In Stock.
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Mathematical Foundations of Nature-Inspired Algorithms (Paperback)
Published by Springer Nature Switzerland AG, Cham, 2019
ISBN 10: 3030169359 ISBN 13: 9783030169350
Language: English
£ 56.33
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Add to basketPaperback. Condition: new. Paperback. This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Mathematical Foundations of Nature-Inspired Algorithms (Paperback)
Published by Springer Nature Switzerland AG, Cham, 2019
ISBN 10: 3030169359 ISBN 13: 9783030169350
Language: English
£ 106.24
Convert currency£ 27.55 shipping from Australia to United KingdomQuantity: 1 available
Add to basketPaperback. Condition: new. Paperback. This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Mathematical Foundations of Nature-Inspired Algorithms
Published by Springer International Publishing, 2019
ISBN 10: 3030169359 ISBN 13: 9783030169350
Language: English
£ 51.32
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Analyzes nature-inspired algorithmsProvides a unified framework of mathematical analysis for convergence and stabilityFeatures methods and techniques for selecting specific algorithms Analyzes nature-inspired algorithmsPro.
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£ 83.60
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