Modelling the thermal behaviour of a building facade using deep learning.

ABSTRACT: This article aims to model the thermal behaviour of a wall using deep learning techniques. The Fourier theoretical model which is traditionally used to model such enclosures is not capable of considering several factors that affect a prediction that is often incorrect. These results motivate us to try to obtain a better thermal model of the enclosure. For this reason, a connexionist model is provided capable of modelling the behaviour of the enclosure from actual observed temperature data. For the training of this model, several measurements have been obtained over the course of more than one year in a specific enclosure, distributing the readings among the different layers of it. In this work, the predictions of both the theoretical model and the connexionist model have been tested, contr

SUBMITTER: Aznar F 

PROVIDER: S-EPMC6303092 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature