A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
A review on time series forecasting techniques for building energy consumption
Energy consumption forecasting for buildings has immense value in energy efficiency and
sustainability research. Accurate energy forecasting models have numerous implications in …
sustainability research. Accurate energy forecasting models have numerous implications in …
Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods
EM de Oliveira, FLC Oliveira - Energy, 2018 - Elsevier
In the last decades, the world's energy consumption has increased rapidly due to
fundamental changes in the industry and economy. In such terms, accurate demand …
fundamental changes in the industry and economy. In such terms, accurate demand …
A combination model based on wavelet transform for predicting the difference between monthly natural gas production and consumption of US
W Qiao, W Liu, E Liu - Energy, 2021 - Elsevier
The prediction model's performance in view of the wavelet transform (WT) is affected
because the wavelet basis function (WBF) and its orders and layers are determined …
because the wavelet basis function (WBF) and its orders and layers are determined …
Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders
Energy consumption in buildings is increasing because of social development and
urbanization. Forecasting the energy consumption in buildings is essential for improving …
urbanization. Forecasting the energy consumption in buildings is essential for improving …
A seasonal GM (1, 1) model for forecasting the electricity consumption of the primary economic sectors
ZX Wang, Q Li, LL Pei - Energy, 2018 - Elsevier
To accurately predict the seasonal fluctuations of the electricity consumption of the primary
economic sectors, we propose a seasonal grey model (SGM (1, 1) model) based on the …
economic sectors, we propose a seasonal grey model (SGM (1, 1) model) based on the …
Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm
S Barak, SS Sadegh - International Journal of Electrical Power & Energy …, 2016 - Elsevier
Energy consumption is on the rise in developing economies. In order to improve present and
future energy supplies, forecasting energy demands is essential. However, lack of accurate …
future energy supplies, forecasting energy demands is essential. However, lack of accurate …
A review on prognostic techniques for non-stationary and non-linear rotating systems
MS Kan, ACC Tan, J Mathew - Mechanical Systems and Signal Processing, 2015 - Elsevier
The field of prognostics has attracted significant interest from the research community in
recent times. Prognostics enables the prediction of failures in machines resulting in benefits …
recent times. Prognostics enables the prediction of failures in machines resulting in benefits …
Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods
P Tüfekci - International Journal of Electrical Power & Energy …, 2014 - Elsevier
Predicting full load electrical power output of a base load power plant is important in order to
maximize the profit from the available megawatt hours. This paper examines and compares …
maximize the profit from the available megawatt hours. This paper examines and compares …
A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India
M Barman, NBD Choudhury, S Sutradhar - Energy, 2018 - Elsevier
In today's restructuring electricity market, short-term load forecasting (STLF) is an essential
tool for the electricity utilities to predict future scenario and act towards a profitable policy …
tool for the electricity utilities to predict future scenario and act towards a profitable policy …