Prediction model of electrical energy consumption in conventional residential buildings using ANN and ANFIS
- سال انتشار: 1402
- محل انتشار: مجله آنالیز غیر خطی و کاربردها، دوره: 14، شماره: 1
- کد COI اختصاصی: JR_IJNAA-14-1_214
- زبان مقاله: انگلیسی
- تعداد مشاهده: 195
نویسندگان
Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Tehran, Iran
Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Tehran, Iran
Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Tehran, Iran
چکیده
The energy consumption of a residential building is considered in terms of energy use and efficiency. Therefore, forecasting the energy consumption of buildings has been raised as a challenge in recent decades. In a residential home, electricity consumption can have recognizable patterns daily, monthly, or yearly depending on living conditions and daily habits and events. In this research, artificial neural network (ANN) and adaptive fuzzy-neural inference system (ANFIS) have been performed using MATLAB software to predict building energy consumption. Also, random data collected based on the criteria obtained from the hourly electricity consumption of conventional residential buildings in Tehran has been used. In order to evaluate and measure the performance of this model, statistical indicators have been used. According to the applied settings (type of learning, number of steps, and error tolerance), the system error rate is calculated based on MSE, RMSE, μ, σ, and R statistical indicators and the results of energy consumption forecast in three buildings with high accuracy and correlation coefficient. R is more than ۹۸%. The output of this research is an intelligent combined system of ANN and ANFIS. The obtained values well show the ability of this model to estimate energy consumption in the mentioned buildings with high accuracy.کلیدواژه ها
Residential Buildings, Electricity Consumption, Artificial Neural Network(ANN), Adaptive Neural Fuzzy Inference System(ANFIS)اطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.