Shulph Ink
Internet of Energy for Smart Cities: Machine Learning Models and Techniques
Internet of Energy for Smart Cities: Machine Learning Models and Techniques
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Excellent- More about Internet of Energy for Smart Cities: Machine Learning Models and Techniques
Machine learning approaches can optimize IoE networks in smart cities, addressing research gaps like demand response management and resource utilization. This book provides in-depth knowledge and real-life case studies for graduate students and researchers in computer science, electrical engineering, and related fields.
Format: Hardback
Length: 302 pages
Publication date: 20 July 2021
Publisher: Taylor & Francis Ltd
Machine learning approaches hold immense potential in addressing the ever-evolving demands of large Internet-of-Energy (IoE) networks, particularly in the context of smart cities. This book serves as a comprehensive guide, focusing on leveraging machine learning techniques to provide innovative solutions for IoE networks in smart cities. By addressing various research gaps, such as demand response management, resource management, and efficient utilization of the underlying ICT network, this book aims to impart deep technical knowledge to readers, enabling them to pursue diverse research problems within this field. Furthermore, real-life case studies and examples are provided to make the concepts relatable and applicable to practical scenarios. With a target audience of Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunications Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book offers a comprehensive exploration of IoE and smart cities, highlighting the role of machine learning in optimizing grid operations within smart city environments.
Weight: 630g
Dimension: 159 x 241 x 25 (mm)
ISBN-13: 9780367497750
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