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Authors: Àngela Nebot and Francisco Mugica

Affiliation: Technical University of Catalonia, Spain

ISBN: 978-989-8565-69-3

Keyword(s): Energy Performance, Heating and Cooling Load, Fuzzy Inductive Reasoning (FIR), Adaptive Neuro-Fuzzy Inference System (ANFIS).

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 on es 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. (More)

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Paper citation in several formats:
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

@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},
}

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

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