In this paper, we present an investigation of the possibility to use a neural network combined with a quasi-physical description in order to predict the annual ...

To create an accurate load model for each class, the loads were classified based on running loads as a function of annual loads. Fur- thermore, to account ...

In the present study, simple polynomial function is used to estimate the annual energy demand as a function of building envelope physical and geometric ...

This article presents a comparative analysis of two prominent machine learning techniques for predicting electricity consumption in workplace lighting systems.

By using the 4th polynomial function that have two double radix and a feature the f(x) = a4 in x = 0 condition, we can calculate annual building load very ...

In this paper, we review the application of machine learning techniques in building load prediction under the organization and logic of the machine learning, ...

Using SVM's as a method of building energy consumption regression has recently become popular in energy modeling literature (Ahmad et al. 2014). Ahmad ...

### Probabilistic Load Forecasting of Adaptive Multiple Polynomial ...

iopscience.iop.org › article › pdf

The load forecasting interval under different scenarios is given and analyzed by using dummy variables. At last, the method is validated based on the history ...

Nov 10, 2020 ¡¤ To address these issues, first, we pass the input data through a preprocessing layer where the number of features increased using a polynomial ...

Oct 2, 2018 ¡¤ This paper provides a substantial review on the four main ML approaches including artificial neural network, support vector machine, Gaussian-based regressions ...