کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6729920 504008 2016 32 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Application of neural networks for evaluating energy performance certificates of residential buildings
ترجمه فارسی عنوان
استفاده از شبکه های عصبی برای ارزیابی گواهی های عملکرد انرژی ساختمان های مسکونی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
The Energy Performance Building Directive 91 of 2002, mandates Member States of the European Union to enforce energy certification of buildings through local legislation. Among the Italian regions, Lombardy has issued predicted energy performance certificates for buildings since 2007 which accumulate to over one million entries. The current study is an attempt to validate a dataset of energy certificates by benefitting from the magnitude of registered buildings. Considering that manual evaluation of every entry is exhaustive and time consuming, artificial neural network is used as a fast and robust alternative for predicting heat demand indicators. Various combinations of input features are compared for selecting a reliable model. The number of inputs and hidden neurons are also optimized in order to achieve better accuracy. Results show that using 12 variables from an energy certificate is sufficient for estimating the related heat demand indicator. Regarding the stochastic initialization of neural networks, a set of 100 models are trained for obtaining a frequency distribution and confidence interval. Final results indicate that about 95% of entries fall within ±3 confidence intervals.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 125, 1 August 2016, Pages 45-54
نویسندگان
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