Big Data Analytics for Cyber-Physical System in Smart City : BDCPS 2020, 28-29 December 2020, Shanghai, China / edited by Mohammed Atiquzzaman, Neil Yen, Zheng Xu
Contributor(s): Atiquzzaman, Mohammed, editor literario | Yen, Neil, editor literario | Xu, Zheng, editor literario | SpringerLink
Material type:
E-bookSeries: (Advances in Intelligent Systems and Computing, 2194-5357; 1303).Publisher: Singapore : Springer International Publising, 2021Edition: First edition 2021.Description: 1 recurso en línea (XLII, 1830 páginas) : 520 ilustraciones, 268 ilustraciones a color.ISBN: 9789813345720.Subject: Datos masivos -- Congresos y asambleas
Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)
Abstract: This book gathers a selection of peer-reviewed papers presented at the second Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020) conference, held in Shanghai, China, on 28-29 December 2020. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.9.B45 2021 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.26042144 |
This book gathers a selection of peer-reviewed papers presented at the second Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020) conference, held in Shanghai, China, on 28-29 December 2020. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
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