A novel method for nZEB internal coverings design based on neural networks

Abstract

Research from the International Energy Agency about indoor ambiences and nearly zero energy buildings (nZEB) in the past has been centred on different aspects such as the prediction of indoor conditions as a function of the weather using laboratory material properties for simulations and real sampled data for validation. Thus, it is possible to use real data for defining behavioural groups of indoor ambiences as a function of real vapour permeability of internal coverings. However, this method is not suitable for modelling it and predicting its behaviour under weather changes, which is of interest to improve the method of selection and use of building construction materials. In this research, artificial intelligence procedures were employed as the first model of permeable coverings material behaviour to provide a newer understanding of building materials and applications for the generation of new control procedures between the mechanical and electronic point of view of building construction materials.