This study proposes hybrid machine learning (ML) models to predict the daily urban water consumption scenario in a neighborhood Brazilian city. The framework evaluates various signal decomposition modes, including empirical wavelet transform (EWT), …
Electroencephalography (EEG) is an exam widely adopted to monitor cerebral activities regarding external stimuli, and its signals compose a nonlinear dynamical system. There are many difficulties associated with EEG analysis. For example, noise can …
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 …
Blood cells can be separated into three types: erythrocytes, leukocytes and platelets, and to evaluate the health of a patient, a Complete Blood Count (CBC) is necessary. CBC is amongst the most performed tests worldwide, and when evaluated manually …
Time series forecasting is an essential approach for businesses and researchers to make informed decisions by predicting future trends and patterns in a given time series data. Nevertheless, forecasting time series accurately can be challenging due …
Efficient models for short-term load forecasting (STLF) plays a crucial role in establishing the companies’ energetic planning due to their importance in electric power distribution and generation systems. An ensemble learning model based on dual …
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 …
The development and expansion of clean energy, such as wind energy, are important in the preservation of the environment and development of local economies and an alternative to hydroelectric and thermal energies. In this respect, the development of …
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, prediction of wind speed with …
The Coronavirus disease 2019 (COVID-19) is a disease responsible for infecting millions of people since the first notification until nowadays. Developing efficient short-term forecasting models allow knowing the number of future COVID-19 cases. In …