Search Results - "Joao de Oliveira, F. L."

An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis by Leite, Denis, Martins, Aldonso, Rativa, Diego, De Oliveira, Joao F. L., Maciel, Alexandre M. A.

“…This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time Fault Detection and Diagnosis (RT-FDD). The approach’s particular…”
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A Hybrid Swarm-Based System for Commodity Price Forecasting During The Covid-19 Pandemic by Xavier, Andre L. S., Fernandes, Bruno J. T., De Oliveira, Joao F. L.

“…Commodity price forecasting is an essential task for defining economic strategies to reduce the impact of inflation in several countries. During the covid-19…”
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Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble by de Mattos Neto, Paulo S. G., de Oliveira, João F. L., Bassetto, Priscilla, Siqueira, Hugo Valadares, Barbosa, Luciano, Alves, Emilly Pereira, Marinho, Manoel H. N., Rissi, Guilherme Ferretti, Li, Fu

“…The employment of smart meters for energy consumption monitoring is essential for planning and management of power generation systems. In this context,…”
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A Hybrid System Based on Dynamic Selection for Time Series Forecasting by de Oliveira, Joao F. L., Silva, Eraylson G., de Mattos Neto, Paulo S. G.

“…Hybrid systems, which combine statistical and machine learning (ML) techniques using residual (error forecasting) modeling, have been highlighted in the…”
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Selection of Temporal Lags for Predicting Riverflow Series from Hydroelectric Plants Using Variable Selection Methods by Siqueira, Hugo, Macedo, Mariana, Tadano, Yara de Souza, Alves, Thiago Antonini, Stevan, Sergio L., Oliveira, Domingos S., Marinho, Manoel H.N., Neto, Paulo S.G. de Mattos, Oliveira,  João F. L. de, Luna, Ivette, Filho, Marcos de Almeida Leone, Sarubbo, Leonie Asfora, Converti, Attilio

“…The forecasting of monthly seasonal streamflow time series is an important issue for countries where hydroelectric plants contribute significantly to electric…”
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Solar Irradiance Forecasting Using Dynamic Ensemble Selection by de O. Santos, Domingos S., de Mattos Neto, Paulo S. G., de Oliveira, João F. L., Siqueira, Hugo Valadares, Barchi, Tathiana Mikamura, Lima, Aranildo R., Madeiro, Francisco, Dantas, Douglas A. P., Converti, Attilio, Pereira, Alex C., de Melo Filho, José Bione, Marinho, Manoel H. N.

“…Solar irradiance forecasting has been an essential topic in renewable energy generation. Forecasting is an important task because it can improve the planning…”
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A hybrid evolutionary decomposition system for time series forecasting by de Oliveira, João F.L., Ludermir, Teresa B.

“…In the field of time series forecasting, the combination of linear and nonlinear models has been explored to improve the accuracy of predictions when compared…”
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Evolutionary Hybrid System for Energy Consumption Forecasting for Smart Meters by Izidio, Diogo M. F., de Mattos Neto, Paulo S. G., Barbosa, Luciano, de Oliveira, João F. L., Marinho, Manoel Henrique da Nóbrega, Rissi, Guilherme Ferretti

“…The usage of smart grids is growing steadily around the world. This technology has been proposed as a promising solution to enhance energy efficiency and…”
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Use of machine learning and multilevel analysis in hierarchical approaches of public expenditure forecasting by Neto, Jose Ivo Carille, Neto, Fernando B. de L., Joao de Oliveira, F. L.

“…On the one hand, public expenditure can be decomposed into several levels of expenditure regarding each administrative unit and expenditure nature groups that…”
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An intelligent hybridization of ARIMA with machine learning models for time series forecasting by de O. Santos Júnior, Domingos S., de Oliveira, João F.L., de Mattos Neto, Paulo S.G.

“…The development of accurate forecasting systems can be challenging in real-world applications. The modeling of real-world time series is a particularly…”
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Early detection of students at risk of failure from a small dataset by Leite, Denis, Filho, Edson, de Oliveira, Joao F. L., Carneiro, Rodrigo E., Maciel, Alexandre

“…Predicting that a student is likely to fail in a course is critical for performing early interventions, prevent dropout and increase performance on distance…”
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Heterogeneous Ensemble for Multi-Step Solar Irradiance Forecasting in Brazilian's Sites by Santos, Domingos Savio de O., Dantas, Douglas A. P., de Mattos Neto, Paulo S. G., Siqueira, Hugo Valadares, Lima, Aranildo R., Madeiro, Francisco, de Oliveira, Joao. F. L., Pereira, Alex C., Marinho, Manoel H. N.

“…Multi-step solar irradiance forecast is an important part of a successful power grid management. However that forecast can be difficult due to nonlinear…”
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Swarm Based Ensembles for Time Series Residual Forecasting by de Holanda, Rafael Bergamo B., de Oliveira, Joao F. L.

“…The forecasting of residual series has become a promising approach to improve the accuracy of forecasting systems. One important aspect of residual forecasting…”
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A hybrid sequential system for inflation forecasting by Xavier, Andre L. S, Fernandes, Bruno J. T., de Oliveira, Joao F. L.

“…Forecasting price indexes of the economy has received an attention from scholars and policy makers due to its significant effect on various sectors and…”
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An adaptive hybrid system using deep learning for wind speed forecasting by de Mattos Neto, Paulo S.G., de Oliveira, João F.L., de O. Santos Júnior, Domingos S., Siqueira, Hugo Valadares, Marinho, Manoel H.N., Madeiro, Francisco

“…The integration of wind power with traditional electricity grids is challenging because of the volatile and intermittent nature of wind speed. Consequently,…”
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