کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6733139 | 504053 | 2014 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation](/preview/png/6733139.png)
چکیده انگلیسی
The several parameters affect the heat load of a building; geometry, construction, layout, climate and the users. These parameters are complex and interrelated. Comprehensive models are needed to understand relationships among the parameters that can handle non-linearities. The aim of this study is to predict heat load of existing buildings benefiting from width/length ratio, wall overall heat transfer coefficient, area/volume ratio, total external surface area, total window area/total external surface area ratio by using artificial neural networks and compare the results with a building energy simulation tool called KEP-IYTE-ESS developed by Izmir Institute of Technology. A back propagation neural network algorithm has been preferred and both simulation tools were applied to 148 residential buildings selected from 3 municipalities of Izmir-Turkey. Under the given conditions, a good coherence was observed between artificial neural network and building energy simulation tool results with a mean absolute percentage error of 5.06% and successful prediction rate of 0.977. The advantages of ANN model over the energy simulation software are observed as the simplicity, the speed of calculation and learning from the limited data sets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 85, December 2014, Pages 115-125
Journal: Energy and Buildings - Volume 85, December 2014, Pages 115-125
نویسندگان
Cihan Turhan, Tugce Kazanasmaz, Ilknur Erlalelitepe Uygun, Kenan Evren Ekmen, Gulden Gokcen Akkurt,