Nature inspired computing wireless (5 Ergebnisse)
Sprache: Englisch
Verlag: Springer Singapore, 2021
Serie: Buch 3 von 23 - Springer Tracts in Nature-Inspired Computing
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Nature Inspired Computing for Wireless Sensor Networks
De, Debashis|Mukherjee, Amartya|Kumar Das, Santosh|Dey, Nilanjan
Sprache: Englisch
Verlag: Springer Singapore, 2020
Serie: Buch 3 von 23 - Springer Tracts in Nature-Inspired Computing
- Hardcover
Anbieter: moluna, Greven, Deutschlandmoluna
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EUR 136,16
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Gebunden. Zustand: New.
Sprache: Englisch
Verlag: Springer, 2021
Serie: Buch 3 von 23 - Springer Tracts in Nature-Inspired Computing
- Softcover
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Taschenbuch. Zustand: Neu. Nature Inspired Computing for Wireless Sensor Networks | Debashis De (u. a.) | Taschenbuch | Springer Tracts in Nature-Inspired Computing | xiv | Englisch | 2021 | Springer | EAN 9789811521270 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]ha…rtmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, 2020
Serie: Buch 3 von 23 - Springer Tracts in Nature-Inspired Computing
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents nature inspired computing applications for the wireless sensor network (WSN). Although the use of WSN is increasing rapidly, it has a number of limitations in the context of battery issue, distraction, low communication speed, and securit…y. This means there is a need for innovative intelligent algorithms to address these issues.The book is divided into three sections and also includes an introductory chapter providing an overview of WSN and its various applications and algorithms as well as the associated challenges. Section 1 describes bio-inspired optimization algorithms, such as genetic algorithms (GA), artificial neural networks (ANN) and artificial immune systems (AIS) in the contexts of fault analysis and diagnosis, and traffic management. Section 2 highlights swarm optimization techniques, such as African buffalo optimization (ABO), particle swarm optimization (PSO), and modified swarm intelligence technique for solving the problems of routing,network parameters optimization, and energy estimation. Lastly, Section 3 explores multi-objective optimization techniques using GA, PSO, ANN, teaching-learning-based optimization (TLBO), and combinations of the algorithms presented. As such, the book provides efficient and optimal solutions for WSN problems based on nature-inspired algorithms.
Sprache: Englisch
Verlag: Springer, Springer, 2021
Serie: Buch 3 von 23 - Springer Tracts in Nature-Inspired Computing
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 168,73
EUR 63,08 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents nature inspired computing applications for the wireless sensor network (WSN). Although the use of WSN is increasing rapidly, it has a number of limitations in the context of battery issue, distraction, low communication speed, and…security. This means there is a need for innovative intelligent algorithms to address these issues.The book is divided into three sections and also includes an introductory chapter providing an overview of WSN and its various applications and algorithms as well as the associated challenges. Section 1 describes bio-inspired optimization algorithms, such as genetic algorithms (GA), artificial neural networks (ANN) and artificial immune systems (AIS) in the contexts of fault analysis and diagnosis, and traffic management. Section 2 highlights swarm optimization techniques, such as African buffalo optimization (ABO), particle swarm optimization (PSO), and modified swarm intelligence technique for solving the problems of routing,network parameters optimization, and energy estimation. Lastly, Section 3 explores multi-objective optimization techniques using GA, PSO, ANN, teaching-learning-based optimization (TLBO), and combinations of the algorithms presented. As such, the book provides efficient and optimal solutions for WSN problems based on nature-inspired algorithms.
