P
Paulo S. G. de Mattos Neto
Researcher at Federal University of Pernambuco
Publications - 56
Citations - 690
Paulo S. G. de Mattos Neto is an academic researcher from Federal University of Pernambuco. The author has contributed to research in topics: Time series & Artificial neural network. The author has an hindex of 11, co-authored 50 publications receiving 386 citations. Previous affiliations of Paulo S. G. de Mattos Neto include Universidade de Pernambuco.
Papers
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Journal ArticleDOI
An intelligent hybridization of ARIMA with machine learning models for time series forecasting
Domingos S. de O. Santos Júnior,Domingos S. de O. Santos Júnior,João Fausto Lorenzato de Oliveira,Paulo S. G. de Mattos Neto +3 more
TL;DR: This work proposes a hybrid system that searches for a suitable function to combine the forecasts of linear and nonlinear models and attains superior performance when compared with single and hybrid models in the literature.
Journal ArticleDOI
Correcting and combining time series forecasters
TL;DR: A two-step method for correcting and combining forecasting models, using single ARIMA and artificial neural networks models for Dow Jones Industrial Average Index, S&P500 Index, Google Stock Value, and Nasdaq Index series illustrate the usefulness of the proposed framework.
Journal ArticleDOI
Hybrid intelligent system for air quality forecasting using phase adjustment
TL;DR: The approach is data-driven and only uses the past values of the pollutant concentrations to predict the next day concentration; in other words, it does not require any exogenous information.
Journal ArticleDOI
Error modeling approach to improve time series forecasters
Paulo Renato Alves Firmino,Paulo S. G. de Mattos Neto,Paulo S. G. de Mattos Neto,Tiago A. E. Ferreira +3 more
TL;DR: Applications involving ARIMA and ANN forecasters for Dow Jones Industrial Average Index, S&P500 Index, Google Stock Value, Nasdaq Index, Wolf׳s Sunspot, and Canadian Lynx data series indicate the usefulness of the proposed framework.
Journal ArticleDOI
Nonlinear combination method of forecasters applied to PM time series
TL;DR: A Nonlinear Combination (NoLiC) method to combine forecasters is proposed and results show that the NoLiC method reaches superior results when compared with literature works.