A survey on data mining techniques applied to energy time series forecasting
Data mining has become an essential tool during the last decade to analyze large 1 sets of data. The variety of techniques it includes and the successful results obtained in 2 many application fields, make this family of approaches powerful and widely used. In 3 particular, this work explores the application of these techniques to time series forecasting. 4 Although classical statistical based methods provides reasonably good results, the result of 5 the application of data mining outperforms those of classical ones. Hence, this work faces 6 two main challenges: i) to provide a compact mathematical formulation of the mainly used 7 techniques, ii) to review the latest works of time series forecasting and, as case study, those 8 related to electricity price and demand markets. 9