Affiliations: [a] Electromechanic Engineering Department, University of Burgos, Burgos, Spain | [b] Department of Civil Engineering, University of Burgos, Burgos, Spain | [c] Computer Science Department, University of Oviedo, Gijón, Spain
Correspondence:
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Corresponding author: Dr. José Ramón Villar, Associate Professor, Computer Science Department, University of Oviedo, Campus de Viesques s/n 33204 Gijón, Spain. Tel.: +34 985 182597; Fax: +34 958 181986; E-mail: villarjose@uniovi.es.
Abstract: The detection of thermal insulation failures in buildings in operation responds to the challenge of improving building energy efficiency. This multidisciplinary study presents a novel four-step soft computing knowledge identification model called IKBIS to perform thermal insulation failure detection. It proposes the use of Exploratory Projection Pursuit methods to study the relation between input and output variables and data dimensionality reduction. It also applies system identification theory and neural networks for modeling the thermal dynamics of the building. Finally, the novel model is used to predict dynamic thermal biases, and two real cases of study as part of its empirical validation.
