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Wind Energy Multi-Step Ahead Forecasting Based on Variational Mode Decomposition

Wind energy is one of the sources which 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, prediction of 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 …

Multi-step ahead Bitcoin Price Forecasting Based on VMD and Ensemble Learning Methods

Bitcoin is the leading currency in the cryptocurrency market capturing attention worldwide. Forecasting the Bitcoin price as accurate as possible is essential, but due to its high volatility this task is challenging. Many researchers try, through the …

Solar Power Forecasting Based on Ensemble Learning Methods

Alternative energy sources are becoming more and more common around the world. In order to reduce environmental pollution and CO 2 emissions, in addition to being an ideal solution to overcome the energy crisis. In this context, power energy stands …

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 …

Very short-term wind energy forecasting based on stacking ensemble

Wind power generation is one of the technologies of electric production which still in development in Brazil, however, it already has a great penetration in the national energy matrix, representing 13.98% of the national energy consumption in Brazil. …