Language: Arabic
Published by Createspace Independent Publishing Platform, 2013
ISBN 10: 1489572198 ISBN 13: 9781489572196
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Language: Arabic
Published by Createspace Independent Publishing Platform, 2013
ISBN 10: 1489572198 ISBN 13: 9781489572196
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Language: Arabic
Published by Createspace Independent Publishing Platform, 2013
ISBN 10: 1489572198 ISBN 13: 9781489572196
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New.
Language: Arabic
Published by Createspace Independent Publishing Platform, 2013
ISBN 10: 1489572198 ISBN 13: 9781489572196
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Language: English
Published by Taylor & Francis Ltd, 2021
ISBN 10: 0367782863 ISBN 13: 9780367782863
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Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 326 pages. 9.21x6.14x0.67 inches. In Stock.
Seller: moluna, Greven, Germany
Condition: New. Prashant K. Srivastava, PhD, research scientist, ESSIC/NASA Goddard Space Flight Center, Greenbelt, Maryland, USADawei Han, PhD, professor of hydroinformatics, Department of Civil Engineering, University of Bristol, UK.
Language: English
Published by Taylor & Francis Ltd Mär 2021, 2021
ISBN 10: 0367782863 ISBN 13: 9780367782863
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Language: English
Published by Elsevier Science Publishing Co Inc, 2022
ISBN 10: 0128234571 ISBN 13: 9780128234570
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 692 | Sprache: Englisch | Produktart: Bücher | This book presents select peer-reviewed proceedings of the International Conference on Innovation in Smart and Sustainable Infrastructure (ISSI2022). The contents focus on smart infrastructure and cites, construction and infrastructure project management, application of building information modelling, sustainable materials and methods for road construction, smart technologies, applications and services for transportation systems, remote sensing and GIS for water resources management, climate change and prediction analysis, model simulation and analysis, seismic engineering and soil dynamics, innovation geo-materials and geosynthetics, computational geotechnics, emerging technologies in smart mobility and transport planning, among others. This volume will be useful for researchers and professionals in civil engineering and allied fields.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Language: English
Published by Bentham Science Publishers, 2018
ISBN 10: 1608055558 ISBN 13: 9781608055555
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 156 pages. 11.00x8.50x0.37 inches. In Stock.
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Language: English
Published by Springer Nature Singapore, 2021
ISBN 10: 9811649626 ISBN 13: 9789811649622
Seller: Buchpark, Trebbin, Germany
Condition: Hervorragend. Zustand: Hervorragend | Seiten: 268 | Sprache: Englisch | Produktart: Bücher | Recently machine learning schemes have attained significant attention as key enablers for next-generation wireless systems. Currently, wireless systems are mostly using machine learning schemes that are based on centralizing the training and inference processes by migrating the end-devices data to a third party centralized location. However, these schemes lead to end-devices privacy leakage. To address these issues, one can use a distributed machine learning at network edge. In this context, federated learning (FL) is one of most important distributed learning algorithm, allowing devices to train a shared machine learning model while keeping data locally. However, applying FL in wireless networks and optimizing the performance involves a range of research topics. For example, in FL, training machine learning models require communication between wireless devices and edge servers via wireless links. Therefore, wireless impairments such as uncertainties among wireless channel states, interference, and noise significantly affect the performance of FL. On the other hand, federated-reinforcement learning leverages distributed computation power and data to solve complex optimization problems that arise in various use cases, such as interference alignment, resource management, clustering, and network control. Traditionally, FL makes the assumption that edge devices will unconditionally participate in the tasks when invited, which is not practical in reality due to the cost of model training. As such, building incentive mechanisms is indispensable for FL networks. This book provides a comprehensive overview of FL for wireless networks. It is divided into three main parts: The first part briefly discusses the fundamentals of FL for wireless networks, while the second part comprehensively examines the design and analysis of wireless FL, covering resource optimization, incentive mechanism, security and privacy. It also presents several solutions based on optimizationtheory, graph theory, and game theory to optimize the performance of federated learning in wireless networks. Lastly, the third part describes several applications of FL in wireless networks.