Decomposition

Variational mode decomposition and bagging extreme learning machine with multi-objective optimization for wind power forecasting

A wind power forecast is an useful support tool for planning and operating wind farm production, facilitating decisions regarding maintenance and load share. This paper presents an evaluation of a cooperative method, which uses a time series …

Seasonal-trend and multiobjective ensemble learning model for water consumption forecasting

Water consumption forecasting is essential for the development of efficient city planning. Due to the non-linearities and relations of the water consumption with different factors the development of an accurate forecasting system is challenging. This …

A novel decomposition-ensemble learning framework for multi-step ahead wind energy forecasting

Wind energy is one of the sources which is still in development in Brazil. However, it already represents 17% of the National Interconnected System. Due to the high level of uncertainty and fluctuations in wind speed, predicting wind energy with high …

Electricity energy price forecasting based on hybrid multi-stage heterogeneous ensemble: Brazilian commercial and residential cases

The development of accurate models to forecast electricity energy prices is a challenge due to the number of factors which can affect this commodity. In this paper, a hybrid multi-stage approach is proposed to forecast multi-stepahead (one, two and …

Forecasting epidemiological time series based on decomposition and optimization approaches

Epidemiological time series forecasting plays an important role in health public system, since it allows managers to develop strategic planning to avoid possible epidemics. In this aspect, a hybrid approach is developed to forecast confirmed cases of …