RT info:eu-repo/semantics/bookPart
T1 Modelling of Heat Flux in Building Using Soft-Computing Techniques
A1 Sedano, Javier
A1 Villar, José Ramón
A1 Curiel Herrera, Leticia Elena
A1 Cal, Enrique de la
A1 Corchado, Emilio
K1 Computational Intelligence
K1 Soft computing Systems
K1 Identification Systems
K1 Artificial Neural Networks
K1 Non-linear Systems
K1 Informática
K1 Computer science
AB Improving the detection of thermal insulation failures in buildings includes the development of models for heating process and fabric gain -heat fluxthrough exterior walls in the building-. Thermal insulation standards are nowcontractual obligations in new buildings, the energy efficiency in the case ofbuildings constructed before the regulations adopted is still an open issue, andthe assumption is that it will be based on heat flux and conductivity measurement. A three-step procedure is proposed in this study that begins by considering the local building and heating system regulations as well as the specific features of the climate zone. Firstly, the dynamic thermal performance of differentvariables is specifically modeled. Secondly, an exploratory projection pursuitmethod called Cooperative Maximum-Likelihood Hebbian Learning is used toextract the relevant features. Finally, a supervised neural model and identification techniques are applied, in order to detect the heat flux through exteriorwalls in the building. The reliability of the proposed method is validated for awinter zone, associated to several cities in Spain.
PB Springer Nature
SN 0302-9743
YR 2010
FD 2010
LK http://hdl.handle.net/10259/8578
UL http://hdl.handle.net/10259/8578
LA eng
NO Trabajo presentado en: International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, 2010
DS Repositorio Institucional de la Universidad de Burgos
RD 09-may-2024