HIGHLIGHTS
- who: Evelina Di Corso and collaborators from the Department of Control and Computer Engineering, Politecnico Torino, Duca degli Abruzzi, Torino, Italy have published the article: METATECH: METeorological Data Analysis for Thermal Energy CHaracterization by Means of Self-Learning Transparent Models, in the Journal: Energies 2018, 11, 1336 of 15/Oct/2014
- what: This work aims at understanding energy consumption in buildings through unsupervised algorithms. The paper presents a statistical sampling method to determine the most useful dwellings to be tested, including several variables concerning airtightness (e_g, climate zone, year of construction, and typology). The analysis . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.