Big Data Intelligence for Smart Applications - Youssef Baddi Youssef Gahi Yassine Maleh Mamoun Alazab Loai Tawalbeh

Big Data Intelligence for Smart Applications

Youssef Baddi (Redaktør) ; Youssef Gahi (Redaktør) ; Yassine Maleh (Redaktør) ; Mamoun Alazab (Redaktør) ; Loai Tawalbeh (Redaktør)

Today, the use of machine intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity. Les mer
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Innbundet
Legg i
Vår pris: 2363,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager

Today, the use of machine intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity.
This book presents the latest advances in big data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.
FAKTA
Utgitt:
Forlag: Springer Nature Switzerland AG
 Innbinding: Innbundet
Språk: Engelsk
Sider: 334
ISBN: 9783030879532
Format: 24 x 16 cm
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Data Quality in the Era of Big Data: A Global Review.- Adversarial Machine Learning, Research Trends and Applications.- Multi-agent Systems for Distributed Data Mining Techniques: An Overview.- Time Series Data Analysis using Deep Learning methods for Smart Cities monitoring.- A Low-Cost IMU-Based Wearable System for Precise Identification of Walk Activity using Deep Convolutional Neural Network.