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Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization
DOAB Contributor

Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization

Author / Organization:
Open Access Books Published 2022 Verification Pending

Overview & Synopsis

In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced modeling and simulation tools makes it possible to derive new technological solutions that can enhance the energy efficiency of systems and that can reduce the ecological footprint. This book compiles 10 novel research works from a Special Issue that was focused on data-driven approaches, machine learning, or artificial intelligence for the modeling, simulation, and optimization of energy systems.

Indexed from repository: Directory of Open Access Books (www.doabooks.org)

Document Information

Document Title Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization
Author / Organization DOAB Contributor
Subject & Discipline passive house
Categories Open Access Books
Publication Year 2022
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website Directory of Open Access Books (www.doabooks.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-292749
Original Source Link Visit Source Page on www.doabooks.org »