Nature-Inspired Optimization Algorithms (ePub)
(Sprache: Englisch)
Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation,...
sofort als Download lieferbar
eBook (ePub)
131.00 €
65 DeutschlandCard Punkte
sammeln
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
Produktdetails
Produktinformationen zu „Nature-Inspired Optimization Algorithms (ePub)“
Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications.
- Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature
- Provides a theoretical understanding and practical implementation hints
- Presents a step-by-step introduction to each algorithm
- Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications
Autoren-Porträt von Xin-She Yang
Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. He is currently a Reader at Middlesex University London, Adjunct Professor at Reykjavik University (Iceland) and Guest Professor at Xi'an Polytechnic University (China). He is an elected Bye-Fellow at Downing College, Cambridge University. He is also the IEEE CIS Chair for the Task Force on Business Intelligence and Knowledge Management, and the Editor-in-Chief of International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO).
Bibliographische Angaben
- Autor: Xin-She Yang
- 2020, 2. Auflage, 310 Seiten, Englisch
- Verlag: Elsevier Science & Techn.
- ISBN-10: 0128219890
- ISBN-13: 9780128219898
- Erscheinungsdatum: 09.09.2020
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: ePub
- Größe: 13 MB
- Mit Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
Kopierschutz
Dieses eBook können Sie uneingeschränkt auf allen Geräten der tolino Familie lesen. Zum Lesen auf sonstigen eReadern und am PC benötigen Sie eine Adobe ID.
Kommentar zu "Nature-Inspired Optimization Algorithms"
0 Gebrauchte Artikel zu „Nature-Inspired Optimization Algorithms“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Nature-Inspired Optimization Algorithms".
Kommentar verfassen