Paulo S. G. de Mattos Neto

Orcid: 0000-0002-2396-7973

According to our database1, Paulo S. G. de Mattos Neto authored at least 45 papers between 2009 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A hybrid system based on ensemble learning to model residuals for time series forecasting.
Inf. Sci., November, 2023

An error correction system for sea surface temperature prediction.
Neural Comput. Appl., June, 2023

A novel multi-objective grammar-based framework for the generation of Convolutional Neural Networks.
Expert Syst. Appl., 2023

Hybrid System with Dynamic Classification for Combining Time Series Forecasts.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2023

2022
A Hybrid System Based on Dynamic Selection for Time Series Forecasting.
IEEE Trans. Neural Networks Learn. Syst., 2022

Multi-human Fall Detection and Localization in Videos.
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.
Proceedings of the RoboCup 2022:, 2022


2021
Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble.
Sensors, 2021

An adaptive hybrid system using deep learning for wind speed forecasting.
Inf. Sci., 2021

EsmamDS: A more diverse exceptional survival model mining approach.
CoRR, 2021

A Dynamic Predictor Selection Method Based on Recent Temporal Windows for Time Series Forecasting.
IEEE Access, 2021

Neural-Based Ensembles for Particulate Matter Forecasting.
IEEE Access, 2021

A Hybrid Model With Error Correction for Wind Speed Forecasting.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2021

A Multi-Objective Grammatical Evolution Framework to Generate Convolutional Neural Network Architectures.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020
A temporal-window framework for modelling and forecasting time series.
Knowl. Based Syst., 2020

Data integration and prediction models of photovoltaic production from Brazilian northeastern.
CoRR, 2020

A hybrid optimized error correction system for time series forecasting.
Appl. Soft Comput., 2020

A Hybrid Nonlinear Combination System for Monthly Wind Speed Forecasting.
IEEE Access, 2020

On the evaluation of dynamic selection parameters for time series forecasting.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Layers Sequence Optimizing for Deep Neural Networks using Multiples Objectives.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Exceptional Survival Model Mining.
Proceedings of the Intelligent Systems - 9th Brazilian Conference, 2020

2019
An intelligent hybridization of ARIMA with machine learning models for time series forecasting.
Knowl. Based Syst., 2019

A Novel Combining-Based Method of Pool Generation for Ensemble Regression Problems.
Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

Hybrid System for Time Series using Iterative Residual Forecasting Models.
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2018
Improving the accuracy of intelligent forecasting models using the Perturbation Theory.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Hybrid Time Series Forecasting Models Applied to Automotive On-Board Diagnostics Systems.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017
Nonlinear combination method of forecasters applied to PM time series.
Pattern Recognit. Lett., 2017

A perturbative approach for enhancing the performance of time series forecasting.
Neural Networks, 2017

2016
Accelerating Families of <i>Fuzzy K-Means</i> Algorithms for Vector Quantization Codebook Design.
Sensors, 2016

Applying a general hybrid intelligent system for ultra-high-frequency stock market forecasting.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Type-2 fuzzy GMM for text-independent speaker verification under unseen noise conditions.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015
Error modeling approach to improve time series forecasters.
Neurocomputing, 2015

2014
Correcting and combining time series forecasters.
Neural Networks, 2014

Measurement of Fitness Function efficiency using Data Envelopment Analysis.
Expert Syst. Appl., 2014

Hybrid intelligent system for air quality forecasting using phase adjustment.
Eng. Appl. Artif. Intell., 2014

2012
Um Método para análise de mercados de ações utilizando séries temporais de índices financeiros.
PhD thesis, 2012

A System Based on Swarm Particle Optimization to Extract Knowledge from Times Series Data.
Proceedings of the 2012 Brazilian Symposium on Neural Networks, 2012

2011
Lag selection for time series forecasting using Particle Swarm Optimization.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

A simulation environment for volatility analysis of developed and in development markets.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010
An intelligent perturbative approach for the time series forecasting problem.
Proceedings of the International Joint Conference on Neural Networks, 2010

An experimental study of fitness function and time series forecasting using artificial neural networks.
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.
Proceedings of the International Joint Conference on Neural Networks, 2009

Combining Artificial Neural Network and Particle Swarm System for time series forecasting.
Proceedings of the International Joint Conference on Neural Networks, 2009

Time series forecasting using a perturbative intelligent system.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009


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