Fuzzy Approaches Improve Predictions of Energy Performance of Buildings

Àngela Nebot, Francisco Mugica

Abstract

The energy consumption in Europe is, to a considerable extent, due to heating and cooling used for domestic purposes. This energy is produced mostly by burning fossil fuels with a high negative environmental impact. The characteristics of a building are an important factor to determine the necessities of heating and cooling loads. Therefore, the study of the relevant characteristics of the buildings with respect to the heating and cooling needed to maintain comfortable indoor air conditions, could be very useful in order to design and construct energy efficient buildings. In previous studies, statistical machine learning approaches have been used to predict heating and cooling loads from eight variables describing the main characteristics of residential buildings which obtained good results. In this research, we present two fuzzy modelling approaches that study the same problem from a different perspective. The prediction results obtained while using fuzzy approaches outperform the ones described in the previous studies. Moreover, the feature selection process of one of the fuzzy methodologies provide interesting insights to the principal building variables causally related to heating and cooling loads.

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Paper Citation


in Harvard Style

Nebot À. and Mugica F. (2013). Fuzzy Approaches Improve Predictions of Energy Performance of Buildings . In Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCEC, (SIMULTECH 2013) ISBN 978-989-8565-69-3, pages 504-511. DOI: 10.5220/0004621405040511


in Bibtex Style

@conference{msccec13,
author={Àngela Nebot and Francisco Mugica},
title={Fuzzy Approaches Improve Predictions of Energy Performance of Buildings},
booktitle={Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCEC, (SIMULTECH 2013)},
year={2013},
pages={504-511},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004621405040511},
isbn={978-989-8565-69-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCEC, (SIMULTECH 2013)
TI - Fuzzy Approaches Improve Predictions of Energy Performance of Buildings
SN - 978-989-8565-69-3
AU - Nebot À.
AU - Mugica F.
PY - 2013
SP - 504
EP - 511
DO - 10.5220/0004621405040511