… a variable to predict power consumption. To predict power consumption, we developed a
Multi-Level Stacked Regression model using pre-processed material information. We trained …

… regression model, but we analyze different kinds of regression models, especially on support
vector regression… .2, and we can acquire the processor utilization with the file “/proc/stat.” In …

… -wide modeling of server power consumption through subsystem models, … energy input to
subsystem energy consumption. We develop a linear regression model that relates processor …

… influences the energy consumption is of great significance for energy demand forecasting. …
optimum regression approach for analyzing weather influence on the energy consumption. …

… Although the regression method is coherent with statistical … to model energy consumption
using linear regression model and … The data pre-processing step includes transformation of the …

… detect abnormal patterns in energy consumption data using estimated consumption intervals.
We … It curates and prepares the data for further processing. The data processing technique …

… other information to regress the energy consumption as a function of house characteristics.
… A neural network is a massively-parallel distributed processor made up of simple processing …

… and data pre-processing methods, the building typologies considered, the targeted …
Nine regression models were prepared and energy consumption forecasting results (MAE) …

… total energy consumption of a building based on deep learning (DL) and compare it to the
standard linear regression (… data can today be stored on Big Data platforms and processed by …

… regression approaches with respect to energy consumption estimation. Furthermore there is
no clear cut as to which approach is superior for energy consumption … energy consumption. …