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)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064


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Research Paper | Civil Engineering | Romania | Volume 3 Issue 12, December 2014

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

D. S. Rusu

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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How to Cite this Article?

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), https://www.ijsr.net/search_index_results_paperid.php?id=SUB14775, Volume 3 Issue 12, December 2014, 1398 - 1401

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