In this paper we address the problem of developing a control strategy to reduce the building energy consumption and reach indoor comfort levels. For this multiple and conflicting objectives optimisation we develop an approach based on stochastic feed-forward neural network models with ARIMA model predictions considered as input variables for networks. Studying real data from a sensorised office located in Rovereto (Italy) we develop the approach and achieve results exhibiting the very good performance of this predictive procedure.
Autori: | |
Data di pubblicazione: | 2015 |
Titolo: | A predictive approach based on neural network models for building automation systems |
Titolo del libro: | Advances in Neural Networks: Computational and Theoretical Issues |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-3-319-18164-6_24 |
Appare nelle tipologie: | 3.1 Articolo su libro |
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