Mathematical Foundations of Nature-Inspired Algorithms (SpringerBriefs in Optimization)
Yang, Xin-She; He, Xing-Shi
ISBN 10: 3030169359 ISBN 13: 9783030169350
Editore: Springer, 2019
Nuovi
Brossura
Da
Best Price, Torrance, CA, U.S.A.
Valutazione del venditore 5 su 5 stelle
Venditore AbeBooks dal 30 agosto 2024
Questo articolo specifico non è più disponibile.
Riguardo questo articolo
Descrizione:
SUPER FAST SHIPPING. Codice articolo 9783030169350
Riassunto:
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Dati bibliografici
Titolo: Mathematical Foundations of Nature-Inspired ...
Casa editrice: Springer
Data di pubblicazione: 2019
Legatura: Brossura
Condizione: New
I migliori risultati di ricerca su AbeBooks
Immagini fornite dal venditore
Mathematical Foundations of Nature-Inspired Algorithms
Editore:
Springer International Publishing, 2019
ISBN 10: 3030169359
ISBN 13: 9783030169350
Nuovo
Brossura
Da: moluna, Greven, Germania
Valutazione del venditore 4 su 5 stelle
Condizione: 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. Codice articolo 279701559
Compra nuovo
EUR 57,15
Spese di spedizione:
EUR 48,99
Da: Germania a: U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Mathematical Foundations of Nature-Inspired Algorithms
Editore:
Springer International Publishing, 2019
ISBN 10: 3030169359
ISBN 13: 9783030169350
Nuovo
Taschenbuch
Da: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Mathematical Foundations of Nature-Inspired Algorithms | Xing-Shi He (u. a.) | Taschenbuch | xi | Englisch | 2019 | Springer International Publishing | EAN 9783030169350 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 115531439
Compra nuovo
EUR 60,05
Spese di spedizione:
EUR 70,00
Da: Germania a: U.S.A.
Quantità: 5 disponibili
Foto dell'editore
Mathematical Foundations of Nature-Inspired Algorithms
Da: Chiron Media, Wallingford, Regno Unito
Valutazione del venditore 4 su 5 stelle
PF. Condizione: New. Codice articolo 6666-IUK-9783030169350
Compra nuovo
EUR 61,66
Spese di spedizione:
EUR 17,62
Da: Regno Unito a: U.S.A.
Quantità: 10 disponibili
Foto dell'editore
Mathematical Foundations of Nature-Inspired Algorithms (SpringerBriefs in Optimization)
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo ABLIING23Mar3113020008478
Compra nuovo
EUR 62,15
Spese di spedizione:
EUR 3,46
In U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Mathematical Foundations of Nature-inspired Algorithms
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 35369970-n
Compra nuovo
EUR 63,35
Spese di spedizione:
EUR 2,29
In U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Mathematical Foundations of Nature-inspired Algorithms
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 35369970-n
Compra nuovo
EUR 63,41
Spese di spedizione:
EUR 17,06
Da: Regno Unito a: U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Mathematical Foundations of Nature-Inspired Algorithms (SpringerBriefs in Optimization)
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9783030169350_new
Compra nuovo
EUR 63,42
Spese di spedizione:
EUR 13,63
Da: Regno Unito a: U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Mathematical Foundations of Nature-Inspired Algorithms
ISBN 10: 3030169359
ISBN 13: 9783030169350
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783030169350
Compra nuovo
EUR 64,19
Spese di spedizione:
EUR 60,98
Da: Germania a: U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Mathematical Foundations of Nature-Inspired Algorithms
ISBN 10: 3030169359
ISBN 13: 9783030169350
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 120 pp. Englisch. Codice articolo 9783030169350
Compra nuovo
EUR 64,19
Spese di spedizione:
EUR 60,00
Da: Germania a: U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Mathematical Foundations of Nature-Inspired Algorithms
Editore:
Springer International Publishing Mai 2019, 2019
ISBN 10: 3030169359
ISBN 13: 9783030169350
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 120 pp. Englisch. Codice articolo 9783030169350
Compra nuovo
EUR 64,19
Spese di spedizione:
EUR 23,00
Da: Germania a: U.S.A.
Quantità: 2 disponibili