Sensitivity based feature selection for recurrent neural network applied to forecasting of heating gas consumption

Martin Macas, Fiorella Lauro, Fabio Moretti, Stefano Pizzuti, Mauro Annunziato, Alessandro Fonti, Gabriele Comodi, Andrea Giantomassi

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

The paper demonstrates the importance of feature selection for recurrent neural network applied to problem of one hour ahead forecasting of gas consumption for office building heating. Although the accuracy of the forecasting is similar for both the feed-forward and the recurrent network, the removal of features leads to accuracy reduction much earlier for the feed-forward network. The recurrent network can perform well even with 50% of features. This brings significant benefits in scenarios, where the neural network is used as a blackbox model of building consumption, which is called by an optimizer that minimizes the consumption. The reduction of input dimensionality leads to reduction of costs related to measurement equipment, but also costs related to data transfer.

Conference

ConferenceInternational Joint Conference on 9th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2014 with 7th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2014 and 5th International Conference on EUropean Transnational Education, ICEUTE 2014
CountrySpain
CityBilbao
Period1/1/14 → …

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Macas, M., Lauro, F., Moretti, F., Pizzuti, S., Annunziato, M., Fonti, A., ... Giantomassi, A. (2014). Sensitivity based feature selection for recurrent neural network applied to forecasting of heating gas consumption. Paper presented at International Joint Conference on 9th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2014 with 7th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2014 and 5th International Conference on EUropean Transnational Education, ICEUTE 2014, Bilbao, Spain. https://doi.org/10.1007/978-3-319-07995-0_26