Machine Learning Applications for Intelligent Energy Management [E-Book] : Invited Chapters from Experts on the Energy Field / edited by Haris Doukas, Vangelis Marinakis, Elissaios Sarmas.
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 a...
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Full text |
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Personal Name(s): | Doukas, Haris, editor |
Marinakis, Vangelis, editor / Sarmas, Elissaios, editor | |
Edition: |
1st edition 2024. |
Imprint: |
Cham :
Springer,
2024
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Physical Description: |
XIV, 226 pages 110 illustrations, 107 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9783031479090 |
DOI: |
10.1007/978-3-031-47909-0 |
Series Title: |
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Learning and Analytics in Intelligent Systems ;
35 |
Subject (LOC): |
- AI-Powered Transformation and Decentralization of the Energy Ecosystem
- An Explainable AI-based Framework for Supporting Decisions in Energy Management
- The big data value chain for the provision of AI-enabled energy analytics services
- MODULAR BIG DATA APPLICATIONS FOR ENERGY SERVICES IN BUILDINGS AND DISTRICTS: DIGITAL TWINS, TECHNICAL BUILDING MANAGEMENT SYSTEMS AND ENERGY SAVINGS CALCULATIONS
- Neural network based approaches for fault diagnosis of photovoltaic systems
- Clustering of building stock
- BIG DATA SUPPORTED ANALYTICS FOR NEXT GENERATION ENERGY PERFORMANCE CERTIFICATES
- Synthetic data on buildings.