Smart city planning by estimating energy efficiency of buildings by extreme learning machine
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CitationErtuğrul, Ö F., Kaya, Y. (2016). Smart city planning by estimating energy efficiency of buildings by extreme learning machine. 2016 4th International Istanbul Smart Grid Congress and Fair (ICSG), 20-21 April 2016, İstanbul, Turkey. https://doi.org/10.1109/sgcf.2016.7492420
Estimation of energy efficiency is one of the major issues in smart city planning. Although, there are some papers about estimation of energy efficiency of the buildings, there is still a requirement of an effective method that can be used in all climatic zones. Therefore, extreme learning method (ELM), which is a training method for single hidden layer neural network, was employed in the dataset that contains the properties of buildings such as shape, area and height and cooling and heating loads were calculated. Achieved results by ELM were compared with the results in the literature and the results obtained by some popular machine learning methods such as artificial neural network, linear regression, and etc. Obtained results by ELM found acceptable.
Source2016 4th International Istanbul Smart Grid Congress and Fair (ICSG)
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