• DocumentCode
    3072228
  • 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
  • fYear
    2012
  • fDate
    20-22 Sept. 2012
  • Firstpage
    265
  • Lastpage
    267
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on
  • Conference_Location
    Belgrade
  • Print_ISBN
    978-1-4673-1569-2
  • Type

    conf

  • DOI
    10.1109/NEUREL.2012.6420032
  • Filename
    6420032
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3072228