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Deep learning in ad-hoc wireless networks

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning in ad-hoc wireless networks/ edited by Gokhan ALTAN, Ipek ABASIKELEŞ TURGUT.
other author:	ALTAN, Gokhan.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	v, 123 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	Recent Deep Learning based Trust Solutions -- Smart Mobility Solutions: The Role of Deep Learning in Traffic Management -- A Survey of Routing Protocols for Low Power and Lossy IoT Network -- Generative Artificial Intelligence Using Deep Learning on Wireless Ad-Hoc Networks.
Contained By:	Springer Nature eBook
Subject:	Ad hoc networks (Computer networks) -
Online resource:	https://doi.org/10.1007/978-3-031-86075-1
ISBN:	9783031860751

Deep learning in ad-hoc wireless networks
Deep learning in ad-hoc wireless networks[electronic resource] /edited by Gokhan ALTAN, Ipek ABASIKELEŞ TURGUT. - Cham :Springer Nature Switzerland :2025. - v, 123 p. :ill. (chiefly color), digital ;24 cm. - Studies in big data,v. 1722197-6511 ;. - Studies in big data ;v. 172..

Recent Deep Learning based Trust Solutions -- Smart Mobility Solutions: The Role of Deep Learning in Traffic Management -- A Survey of Routing Protocols for Low Power and Lossy IoT Network -- Generative Artificial Intelligence Using Deep Learning on Wireless Ad-Hoc Networks.

This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.

ISBN: 9783031860751

Standard No.: 10.1007/978-3-031-86075-1doiSubjects--Topical Terms:

922461
Ad hoc networks (Computer networks)

LC Class. No.: TK5105.77

Dewey Class. No.: 004.685

Deep learning in ad-hoc wireless networks
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245 0 0 $a Deep learning in ad-hoc wireless networks $h [electronic resource] / $c edited by Gokhan ALTAN, Ipek ABASIKELEŞ TURGUT.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a v, 123 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6511 ; $v v. 172
505 0 $a Recent Deep Learning based Trust Solutions -- Smart Mobility Solutions: The Role of Deep Learning in Traffic Management -- A Survey of Routing Protocols for Low Power and Lossy IoT Network -- Generative Artificial Intelligence Using Deep Learning on Wireless Ad-Hoc Networks.
520 $a This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.
650 0 $a Ad hoc networks (Computer networks) $3 922461
650 0 $a Deep learning (Machine learning) $3 3538509
650 1 4 $a Data Engineering. $3 3409361
650 2 4 $a Wireless and Mobile Communication. $3 3338159
650 2 4 $a Big Data. $3 3134868
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Machine Learning. $3 3382522
700 1 $a ALTAN, Gokhan. $3 3784065
700 1 $a Turgut, Ipek Abasikeleş. $3 3784066
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in big data ; $v v. 172. $3 3784067
856 4 0 $u https://doi.org/10.1007/978-3-031-86075-1
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)