A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings

Volume: 13, Issue: 3, Pages: 689 - 705
Published: Jan 24, 2020
Abstract
The international community has largely recognized that the Earth’s climate is changing. Mitigating its global effects requires international actions. The European Union (EU) is leading several initiatives focused on reducing the problems. Specifically, the Climate Action tries to both decrease EU greenhouse gas emissions and improve energy efficiency by reducing the amount of primary energy consumed, and it has pointed to the development of...
Paper Details
Title
A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings
Published Date
Jan 24, 2020
Volume
13
Issue
3
Pages
689 - 705
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