Overview
- Presents novel applications of AI in the domain of building energy efficiency and smart energy management
- Provides detailed paradigms based on real data and real-life applications
- Shows a methodological framework of each application in detail
Part of the book series: Learning and Analytics in Intelligent Systems (LAIS, volume 35)
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About this book
As carbon dioxide (CO2) emissions and other greenhouse gases constantly rise and constitute the main contributor to climate change, temperature rise and global warming, artificial intelligence, big data, Internet of things, and blockchain technologies are enlisted to help enforce energy transition and transform the entire energy sector.
The book at hand presents state-of-the-art developments in artificial intelligence-empowered analytics of energy data and artificial intelligence-empowered application development. Topics covered include a presentation of the various stakeholders in the energy sector and their corresponding required analytic services, such as state-of-the-art machine learning, artificial intelligence, and optimization models and algorithms tailored for a series of demanding energy problems and aiming at providing optimal solutions under specific constraints.
Professors, researchers, scientists, engineers, and students in energy sector-related disciplines are expected to be inspired and benefit from this book, along with readers from other disciplines wishing to learn more about this exciting new field of research.
Keywords
Table of contents (7 chapters)
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Front Matter
Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning Applications for Intelligent Energy Management
Book Subtitle: Invited Chapters from Experts on the Energy Field
Editors: Haris Doukas, Vangelis Marinakis, Elissaios Sarmas
Series Title: Learning and Analytics in Intelligent Systems
DOI: https://doi.org/10.1007/978-3-031-47909-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-031-47908-3Published: 28 January 2024
Softcover ISBN: 978-3-031-47911-3Due: 10 February 2025
eBook ISBN: 978-3-031-47909-0Published: 27 January 2024
Series ISSN: 2662-3447
Series E-ISSN: 2662-3455
Edition Number: 1
Number of Pages: XIV, 226
Number of Illustrations: 3 b/w illustrations, 107 illustrations in colour
Topics: Computational Intelligence, Electrical Engineering, Artificial Intelligence, Energy Policy, Economics and Management