Prediction of Energy Consumption in Residential Buildings Before and After Retrofitting using Artificial Neural Networks
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Civil Engineering | Romania | Volume 3 Issue 12, December 2014 | Popularity: 6.8 / 10


     

Prediction of Energy Consumption in Residential Buildings Before and After Retrofitting using Artificial Neural Networks

D. S. Rusu


Abstract: This paper presents the development of a new method of energy consumption prediction in residential buildings taking into consideration the great differences between the standard modelling simulations and the real conditions. The novelty of this method is that energy consumption is determined based on real data collected from numerous real cases instead of standard old norms, leading to a more accurate prediction. This method takes into consideration the nonlinearity relations between all the measurable variables and the final energy consumption, without being restricted to standards and norms. To this end, several artificial neural networks were built, trained and tested, generating computer software that can be used for verifying and proving the accuracy of the new method in predicting the energy consumption in retrofitting residential buildings.


Keywords: energy consumption, residential, buildings, neural networks


Edition: Volume 3 Issue 12, December 2014


Pages: 1398 - 1401



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D. S. Rusu, "Prediction of Energy Consumption in Residential Buildings Before and After Retrofitting using Artificial Neural Networks", International Journal of Science and Research (IJSR), Volume 3 Issue 12, December 2014, pp. 1398-1401, https://www.ijsr.net/getabstract.php?paperid=SUB14775, DOI: https://www.doi.org/10.21275/SUB14775

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