Title :
Dimensioning the heating system for residential buildings using neural networks
Author :
Lacrama, Dan L. ; Pintea, Florentina A. ; Karnyanszky, M.T.
Author_Institution :
Comput. Sci. Fac., “Tibiscus” Univ. of Timisoara, Timişoara, Romania
Abstract :
This paper is focused on the development of a neural solution to the residential buildings´ heating design. Basically it is about a large and complex design formula which we propose to compute employing a Multilayer Perceptron. The experimental results presented in the fourth section prove neural network can be a good design tool in this area.
Keywords :
building management systems; buildings (structures); multilayer perceptrons; space heating; heating system dimensions; multilayer perceptron; neural networks; residential building heating design; Floors; Space heating; Thermal resistance; Windows; Heating Systems Design; Neural Networks;
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4673-1569-2
DOI :
10.1109/NEUREL.2012.6420032