Ensemble learning

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 …

Wind power forecasting based on bagging extreme learning machine ensemble model

The wind energy forecast is an useful tool for wind farm production planning, and operation, facilitating decision making in terms of maintenance, electricity market clearing, and load sharing. This study proposes a cooperative ensemble learning …

Ensemble learning models coupled with urban mobility information applied to predict COVID-19 incidence cases

The coronavirus disease (COVID-19), according to the World Health Organization, by September 4th, 2020, has infected more than 26 million people, and more than 865 thousand have died from it in the worldwide. It is important to forecast the incidence …

Dengue cases forecasting based on extreme gradient boosting ensemble with coyote optimization

Dengue is considered a public health problem in tropical regions, periodically affecting an increasing number of citizens. Consequently, the development of efficient models is essentials to short and long-term forecasting, supporting health care …

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 …

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 …