In this project, different Statistical and Machine Learning models are compared for the prediction of electricity consumption. The analyzed series consists of 11 months of readings every 10 minutes and the prediction window is 1 month. The models tested were ARIMA, UCM and Machine Learning (SVM, RF).
gianscuri/Electricity_Consumption_Forecasting_ARIMA-UCM-ML
High-frequency time series forecast of electricity consumptions using ARIMA, UCM and ML techniques
MIT