Abstract
The main objective of this study is to develop a more accurate method to estimate the energy consumption of commercial buildings at the design stage. The study is based on the simplified model presented in the Regulation for Energy Efficiency Labelling of Commercial Buildings in Brazil. The first step was to evaluate the feasibility and relevance of more complex statistical modelling techniques, such as the neural network. The second step of the assessment consisted of applying the Latin Hypercube sampling technique to combine the effects of several input parameters. Therefore, results of this work may have a profound impact as artificial neural network may be applied in the future in the Brazilian regulation and many other countries.
Original language | English |
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Title of host publication | Proceedings of BS 2013 |
Subtitle of host publication | 13th Conference of the International Building Performance Simulation Association |
Pages | 644-651 |
Number of pages | 8 |
Publication status | Published - 2013 |
Event | 13th Conference of the International Building Performance Simulation Association, BS 2013 - Chambery, France Duration: 26 Aug 2013 → 28 Aug 2013 |
Conference
Conference | 13th Conference of the International Building Performance Simulation Association, BS 2013 |
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Country/Territory | France |
City | Chambery |
Period | 26/08/13 → 28/08/13 |
Keywords
- Regulation for Energy Efficiency Labelling of Commercial Buildings
- energy consumption
- commercial buildings
- neural networks