Stacking ensemble learning

Beta-hCG test demand forecasting using stacking ensemble-learning and machine learning approaches

Demand forecasting is essential for decision-making, since these forecasts are important inputs for strategic management decisions. In this context, the contribution of this study is to propose a hybrid forecasting framework that combines machine …

Multi-step short-term wind speed forecasting based on multi-stage decomposition coupled with stacking-ensemble learning approach

Wind energy is an emerging source of renewable energy in Brazil. Nevertheless, it already accounts for 17% of the National Interconnected Network. Due to the great intricacy of wind speed variations, it is difficult to predict wind energy with high …

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 …

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 …