*2.3. Methods*

This paper has two main steps to design an electricity load forecasting system: (1) Exploratory data process to investigate correlations between weather parameters and electricity load; (2) Design a machine-learning-based model for electricity load forecasting using the best weather features obtained from step (1). For electricity load forecasting, two machine learning methods were utilized, namely, the Generalized Regression Neural Network (GRNN) and the Support Vector Regression (SVR) techniques (SVR). In the following subsections, we briefly describe these two methods.
