Artificial Neural Networks for Predicting the Energy Behavior of a Building Category
A Powerful Tool for Cost-Optimal Analysis
F. Ascione1, N. Bianco1, R.F. De Masi2, C. De Stasio1, G.M. Mauro1 and G.P. Vanoli2, 1Università degli Studi di Napoli Federico II, Napoli, Italy, 2Università degli Studi del Sannio, Benevento, Italy
Abstract
The reliable assessment of building energy performance requires significant computational times. The chapter handles this issue by proposing an original methodology that employs artificial neural networks (ANNs) to predict the energy behavior of all buildings of an established category. The ANNs are generated in MATLAB by using EnergyPlus simulations for testing and training purposes. The inputs ...
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