Machine Learning as a solution tool for district heating

Autor:	Mugaguren, Mikel Lumbreras, Østergaard, Peter Friis, Fester, Jakob, Martinez, Roberto Garay
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Machine Learning heating system network level heating networks renewable energy district heating
DOI:	10.5281/zenodo.6611524
Popis:	In recent years, Machine Learning has become one of the most used techniques when modelling relationships between different parameters. Inspired by the successful integration of Machine Learning in many other areas, it is beginning to draw attention in the district heating sector as well. The application of Machine Learning in the context of district heating has an obvious potential as a component of tomorrows heating networks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64cb6e6c027f52bb263ca435908e42bf Zobrazit plný text záznamu