2026-04-19T19:59:38Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/85832024-02-06T01:05:26Zcom_10259_3847com_10259_5086com_10259_2604col_10259_3848

Sedano, Javier Curiel Herrera, Leticia Elena Corchado, Emilio Cal, Enrique de la Villar, José Ramón 2024-02-05T12:26:36Z 2024-02-05T12:26:36Z 2010-04 1069-2509 http://hdl.handle.net/10259/8583 10.3233/ICA-2010-0337 1875-8835 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. This research has been partially supported through projects of the Juna of Castilla y León (JCyL): [BU006A08] and Business intelligent for production, Technological Institute of Castilla y León (ITCL) and investment and services agency (ADE), project of the Spanish Ministry of Education and Innovation [CIT-020000-2008-2] and project of Spanish Ministry of Science and Technology [TIN2008-06681-C06-04]. application/pdf eng IOS Press Integrated Computer-Aided Engineering. 2010, V. 17, n. 2, p. 103-115 https://content.iospress.com/articles/integrated-computer-aided-engineering/ica00337 Informática Computer science A soft computing method for detecting lifetime building thermal insulation failures info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/closedAccess Integrated Computer-Aided Engineering 17 2 103 115