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Titolo
A soft computing method for detecting lifetime building thermal insulation failures
Autor(es)
Soggetto
Computer Science
Fecha de publicación
2010
Editore
IOS Press
Citación
Integrated Computer-Aided Engineering. Volumen 17 (2), pp. 103-115. IOS Press.
Resumen
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.
URI
ISSN
1069-2509 (Print) 1875-8835 (Online)
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