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Data-Driven Mining, Learning and Analytics for Secured Smart Cities - Trends and Advances (Paperback, 1st ed. 2021) Loot Price: R4,378
Discovery Miles 43 780
Repayment Terms: R410 pm x 12*
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Data-Driven Mining, Learning and Analytics for Secured Smart Cities - Trends and Advances (Paperback, 1st ed. 2021): Chinmay...

Data-Driven Mining, Learning and Analytics for Secured Smart Cities - Trends and Advances (Paperback, 1st ed. 2021)

Chinmay Chakraborty, Jerry Chun-Wei Lin, Mamoun Alazab

Series: Advanced Sciences and Technologies for Security Applications

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Loot Price R4,378 Discovery Miles 43 780 | Repayment Terms: R410 pm x 12*

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This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Advanced Sciences and Technologies for Security Applications
Release date: April 2022
First published: 2021
Editors: Chinmay Chakraborty • Jerry Chun-Wei Lin • Mamoun Alazab
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 383
Edition: 1st ed. 2021
ISBN-13: 978-3-03-072141-1
Categories: Books > Social sciences > Politics & government > Public administration
Books > Computing & IT > Internet > Network computers
Books > Professional & Technical > Civil engineering, surveying & building > Building construction & materials > Security & fire alarm systems
Books > Computing & IT > Applications of computing > Databases > Data mining
Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 3-03-072141-8
Barcode: 9783030721411

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