Paulo S. G. de Mattos Neto

According to our database, Paulo S. G. de Mattos Neto authored at least 51 papers between 2009 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

EsmamDS: A more diverse exceptional survival model mining approach.

Renato Vimieiro, Juliana Barcellos Mattos, Paulo S. G. de Mattos Neto

Inf. Sci., 2025

2024

A hybrid recursive direct system for multi-step mortality rate forecasting.

Filipe Coelho de Lima Duarte, Paulo S. G. de Mattos Neto, Paulo Renato A. Firmino

J. Supercomput., September, 2024

A dynamic ensemble approach based on trend analysis to COVID-19 incidence forecast.

Jair Paulino de Sales, Paulo S. G. de Mattos Neto, Paulo Renato A. Firmino

Biomed. Signal Process. Control., 2024

On the Sea Surface Temperature Forecasting Problem with Deep Dilation-Erosion-Linear Models.

Ricardo de A. Araújo, Paulo S. G. de Mattos Neto, Nadia Nedjah, Sérgio C. B. Soares

Big Data Res., 2024

An Evolutionary Approach to Forecasting Models Hybridization.

Camila Ascendina, Paulo Salgado Gomes de Mattos Neto, João Fausto Lorenzato de Oliveira, Péricles B. C. de Miranda

Proceedings of the 2024 16th International Conference on Machine Learning and Computing, 2024

A New Ensemble with Partition Size Variation Applied to Wind Speed Time Series.

Diogo M. Almeida, Paulo S. G. de Mattos Neto, Daniel Carvalho da Cunha

Proceedings of the Hybrid Artificial Intelligent Systems - 19th International Conference, 2024

2023

A hybrid system based on ensemble learning to model residuals for time series forecasting.

Domingos S. de O. Junior, Paulo S. G. de Mattos Neto, João F. L. de Oliveira, George D. C. Cavalcanti

Inf. Sci., November, 2023

An error correction system for sea surface temperature prediction.

Ricardo de A. Araújo, Paulo S. G. de Mattos Neto, Nadia Nedjah, Sérgio Castelo Branco Soares

Neural Comput. Appl., June, 2023

A novel multi-objective grammar-based framework for the generation of Convolutional Neural Networks.

Cleber A. C. F. da Silva, Daniel Carneiro Rosa, Péricles B. C. de Miranda, Filipe R. Cordeiro, Tapas Si, André C. A. Nascimento, Rafael Ferreira Leite de Mello, Paulo S. G. de Mattos Neto

Expert Syst. Appl., 2023

Hybrid System with Dynamic Classification for Combining Time Series Forecasts.

Emilly Pereira Alves, Felipe Alberto B. S. Ferreira, Francisco Madeiro, Paulo S. G. de Mattos Neto, João Fausto Lorenzato de Oliveira

Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2023

An Intelligent Dynamic Selection System Based on Nearest Temporal Windows for Time Series Forecasting.

Gabriel Mendes Matos, Paulo S. G. de Mattos Neto

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

2022

A Hybrid System Based on Dynamic Selection for Time Series Forecasting.

João F. L. de Oliveira, Eraylson G. Silva, Paulo S. G. de Mattos Neto

IEEE Trans. Neural Networks Learn. Syst., 2022

Multi-human Fall Detection and Localization in Videos.

Mouglas Eugênio Nasário Gomes, David Macêdo, Cleber Zanchettin, Paulo Salgado Gomes de Mattos Neto, Adriano L. I. Oliveira

Comput. Vis. Image Underst., 2022

Web Soccer Monitor: An Open-Source 2D Soccer Simulation Monitor for the Web and the Foundation for a New Ecosystem.

Mateus F. B. Soares, Tsang Ing Ren, Paulo S. G. de Mattos Neto, Edna Natividade da Silva Barros

Proceedings of the RoboCup 2022:, 2022

A Library and Web Platform for RoboCup Soccer Matches Data Analysis.

Felipe N. A. Pereira, Mateus F. B. Soares, Conceição Rocha, Tales T. Alves, Tiago H. R. P. Gonçalves, José R. da Silva, Tsang Ing Ren, Paulo S. G. de Mattos Neto, Edna Natividade da Silva Barros

Proceedings of the RoboCup 2022:, 2022

2021

Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble.

Paulo S. G. de Mattos Neto, João F. L. de Oliveira, Priscilla Bassetto, Hugo Valadares Siqueira, Luciano Barbosa, Emilly Pereira Alves, Manoel Henrique da Nobrega Marinho, Guilherme Ferretti Rissi, Fu Li

Sensors, 2021

An adaptive hybrid system using deep learning for wind speed forecasting.

Paulo S. G. de Mattos Neto, João F. L. de Oliveira, Domingos S. de O. Junior, Hugo Valadares Siqueira, Manoel Henrique da Nobrega Marinho, Francisco Madeiro

Inf. Sci., 2021

A Dynamic Predictor Selection Method Based on Recent Temporal Windows for Time Series Forecasting.

Eraylson G. Silva, Paulo S. G. de Mattos Neto, George D. C. Cavalcanti

IEEE Access, 2021

Neural-Based Ensembles for Particulate Matter Forecasting.

Paulo S. G. de Mattos Neto, Paulo Renato A. Firmino, Hugo Siqueira, Yara de Souza Tadano, Thiago Antonini Alves, João Fausto Lorenzato de Oliveira, Manoel Henrique da Nobrega Marinho, Francisco Madeiro

IEEE Access, 2021

A Hybrid Model With Error Correction for Wind Speed Forecasting.

Tathiana M. Barchi, Lucas Francesco Piccioni Costa, Erickson Diogo Pereira Puchta, Marcella S. R. Martins, Mauren Louise Sguario C. Andrade, Paulo S. G. de Mattos Neto, Hugo Valadares Siqueira

Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2021

A Multi-Objective Grammatical Evolution Framework to Generate Convolutional Neural Network Architectures.

Cleber A. C. F. da Silva, Daniel Carneiro Rosa, Péricles B. C. de Miranda, Filipe R. Cordeiro, Tapas Si, André C. A. Nascimento, Rafael Ferreira Leite de Mello, Paulo S. G. de Mattos Neto

Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020

A temporal-window framework for modelling and forecasting time series.

Paulo S. G. de Mattos Neto, George D. C. Cavalcanti, Paulo Renato A. Firmino, Eraylson G. Silva, Sérgio R. P. Vila Nova Filho

Knowl. Based Syst., 2020

Data integration and prediction models of photovoltaic production from Brazilian northeastern.

Hugo Abreu Mendes, Henrique Ferreira Nunes, Paulo Salgado Gomes de Mattos Neto

CoRR, 2020

A hybrid optimized error correction system for time series forecasting.

João Fausto Lorenzato de Oliveira, Luciano Demetrio Santos Pacífico, Paulo Salgado Gomes de Mattos Neto, Emanoel Francisco Spósito Barreiros, Cleyton Mário de Oliveira Rodrigues, Adauto Trigueiro de Almeida Filho

Appl. Soft Comput., 2020

A Hybrid Nonlinear Combination System for Monthly Wind Speed Forecasting.

Paulo S. G. de Mattos Neto, João Fausto Lorenzato de Oliveira, Domingos S. de O. Junior, Hugo Valadares Siqueira, Manoel Henrique da Nobrega Marinho, Francisco Madeiro

IEEE Access, 2020

On the evaluation of dynamic selection parameters for time series forecasting.

Eraylson G. Silva, George D. C. Cavalcanti, João Fausto Lorenzato de Oliveira, Paulo S. G. de Mattos Neto

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Layers Sequence Optimizing for Deep Neural Networks using Multiples Objectives.

Paulo S. G. de Mattos Neto, Péricles B. C. de Miranda, George D. C. Cavalcanti, Tapas Si, Filipe R. Cordeiro, Mayara Castro

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Exceptional Survival Model Mining.

Juliana Barcellos Mattos, Eraylson G. Silva, Paulo S. G. de Mattos Neto, Renato Vimieiro

Proceedings of the Intelligent Systems - 9th Brazilian Conference, 2020

2019

An intelligent hybridization of ARIMA with machine learning models for time series forecasting.

Domingos S. de O. Junior, João F. L. de Oliveira, Paulo S. G. de Mattos Neto

Knowl. Based Syst., 2019

A Novel Combining-Based Method of Pool Generation for Ensemble Regression Problems.

Robson D. A. Timoteo, Daniel C. Cunha, Paulo S. G. de Mattos Neto

Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

Hybrid System for Time Series using Iterative Residual Forecasting Models.

Eraylson Galdino da Silva, Paulo Salgado Gomes de Mattos Neto, João Fausto Lorenzato de Oliveira

Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2018

Improving the accuracy of intelligent forecasting models using the Perturbation Theory.

Eraylson G. Silva, Domingos S. de O. Junior, George D. C. Cavalcanti, Paulo S. G. de Mattos Neto

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Hybrid Time Series Forecasting Models Applied to Automotive On-Board Diagnostics Systems.

Diogo M. Almeida, Paulo S. G. de Mattos Neto, Daniel C. Cunha

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017

Nonlinear combination method of forecasters applied to PM time series.

Paulo S. G. de Mattos Neto, George D. C. Cavalcanti, Francisco Madeiro

Pattern Recognit. Lett., 2017

A perturbative approach for enhancing the performance of time series forecasting.

Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira, Aranildo R. Lima, Germano C. Vasconcelos, George D. C. Cavalcanti

Neural Networks, 2017

2016

Accelerating Families of <i>Fuzzy K-Means</i> Algorithms for Vector Quantization Codebook Design.

Edson Mata, Silvio Bandeira, Paulo S. G. de Mattos Neto, Waslon Terllizzie A. Lopes, Francisco Madeiro

Sensors, 2016

Applying a general hybrid intelligent system for ultra-high-frequency stock market forecasting.

Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Type-2 fuzzy GMM for text-independent speaker verification under unseen noise conditions.

Hector N. B. Pinheiro, Sergio R. F. Vieira, Tsang Ing Ren, George D. C. Cavalcanti, Paulo S. G. de Mattos Neto

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

Error modeling approach to improve time series forecasters.

Paulo Renato A. Firmino, Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira

Neurocomputing, 2015

2014

Correcting and combining time series forecasters.

Paulo Renato A. Firmino, Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira

Neural Networks, 2014

Measurement of Fitness Function efficiency using Data Envelopment Analysis.

David Augusto Silva, Gabriela I. L. Alves, Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira

Expert Syst. Appl., 2014

Hybrid intelligent system for air quality forecasting using phase adjustment.

Paulo S. G. de Mattos Neto, Francisco Madeiro, Tiago A. E. Ferreira, George D. C. Cavalcanti

Eng. Appl. Artif. Intell., 2014

2012

Um Método para análise de mercados de ações utilizando séries temporais de índices financeiros.

Paulo Salgado Gomes de Mattos Neto

PhD thesis, 2012

A System Based on Swarm Particle Optimization to Extract Knowledge from Times Series Data.

Henrique Correia Torres Santos, Gabriela I. L. Alves, Neilson F. de Lima, Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira

Proceedings of the 2012 Brazilian Symposium on Neural Networks, 2012

2011

Lag selection for time series forecasting using Particle Swarm Optimization.

Gustavo H. T. Ribeiro, Paulo S. G. de Mattos Neto, George D. C. Cavalcanti, Ing Ren Tsang

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

A simulation environment for volatility analysis of developed and in development markets.

Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira, George D. C. Cavalcanti

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010

An intelligent perturbative approach for the time series forecasting problem.

Paulo S. G. de Mattos Neto, Aranildo R. Lima, Tiago A. E. Ferreira, George D. C. Cavalcanti

Proceedings of the International Joint Conference on Neural Networks, 2010

An experimental study of fitness function and time series forecasting using artificial neural networks.

Aranildo Rodrigues Lima Junior, David Augusto Silva, Paulo Salgado Gomes de Mattos Neto, Tiago A. E. Ferreira

Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2009

A prime step in the time series forecasting with hybrid methods: The fitness function choice.

L. J. Aranildo Rodrigues, Paulo S. G. de Mattos Neto, Tiago A. E. Ferreira

Proceedings of the International Joint Conference on Neural Networks, 2009

Combining Artificial Neural Network and Particle Swarm System for time series forecasting.

Paulo S. G. de Mattos Neto, Gustavo G. Petry, Aranildo Rodrigues Lima Junior, Tiago A. E. Ferreira

Proceedings of the International Joint Conference on Neural Networks, 2009

Time series forecasting using a perturbative intelligent system.

Paulo S. G. de Mattos Neto, Aranildo Rodrigues Lima Junior, Tiago A. E. Ferreira

Proceedings of the Genetic and Evolutionary Computation Conference, 2009