Applying empirical mode decomposition and mutual information to separate stochastic and deterministic influences embedded in signals RA Rios, RF de Mello Signal Processing 118, 159-176, 2016 | 50 | 2016 |
Improving time series modeling by decomposing and analyzing stochastic and deterministic influences RA Rios, RF De Mello Signal Processing 93 (11), 3001-3013, 2013 | 46 | 2013 |
Using CNN to classify spectrograms of seismic events from Llaima volcano (Chile) M Curilem, JP Canário, L Franco, RA Rios 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 45 | 2018 |
In-depth comparison of deep artificial neural network architectures on seismic events classification JP Canario, R Mello, M Curilem, F Huenupan, R Rios Journal of Volcanology and Geothermal Research 401, 106881, 2020 | 44 | 2020 |
Decomposing time series into deterministic and stochastic influences: A survey FSLG Duarte, RA Rios, ER Hruschka, RF de Mello Digital Signal Processing 95, 102582, 2019 | 35 | 2019 |
Using dynamical systems tools to detect concept drift in data streams FG da Costa, RA Rios, RF de Mello Expert Systems with Applications 60, 39-50, 2016 | 33 | 2016 |
FoT-Stream: A Fog platform for data stream analytics in IoT BM Alencar, RA Rios, C Santana, C Prazeres Computer Communications 164, 77-87, 2020 | 23 | 2020 |
Classification of time series generation processes using experimental tools: a survey and proposal of an automatic and systematic approach RP Ishii, RA Rios, RF Mello International Journal of Computational Science and Engineering 6 (4), 217-237, 2011 | 21 | 2011 |
Prediction of hemophilia A severity using a small-input machine-learning framework TJS Lopes, R Rios, T Nogueira, RF Mello NPJ systems biology and applications 7 (1), 22, 2021 | 17 | 2021 |
Data streams are time series: Challenging assumptions J Read, RA Rios, T Nogueira, RF de Mello Brazilian Conference on Intelligent Systems, 529-543, 2020 | 17 | 2020 |
Estimating determinism rates to detect patterns in geospatial datasets RA Rios, L Parrott, H Lange, RF de Mello Remote Sensing of Environment 156, 11-20, 2015 | 17 | 2015 |
Country transition index based on hierarchical clustering to predict next COVID-19 waves RA Rios, T Nogueira, DB Coimbra, TJS Lopes, A Abraham, RF Mello Scientific reports 11 (1), 15271, 2021 | 16 | 2021 |
Discriminating seismic events of the Llaima volcano (Chile) based on spectrogram cross-correlations M Curilem, RF de Mello, F Huenupan, C San Martin, L Franco, ... Journal of Volcanology and Geothermal Research 367, 63-78, 2018 | 16 | 2018 |
TSViz: a data stream architecture to online collect, analyze, and visualize tweets RA Rios, PA Pagliosa, RP Ishii, RF de Mello Proceedings of the Symposium on Applied Computing, 1031-1036, 2017 | 15 | 2017 |
Llaima volcano dataset: In-depth comparison of deep artificial neural network architectures on seismic events classification JP Canário, RF de Mello, M Curilem, F Huenupan, RA Rios Data in brief 30, 105627, 2020 | 13 | 2020 |
Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII TJS Lopes, R Rios, T Nogueira, RF Mello Scientific reports 11 (1), 12625, 2021 | 12 | 2021 |
A systematic literature review on decomposition approaches to estimate time series components RA Rios, RF de Mello INFOCOMP Journal of Computer Science 11 (3-4), 31-46, 2012 | 11 | 2012 |
Temporal gap statistic: A new internal index to validate time series clustering RG Ribeiro, R Rios Chaos, Solitons & Fractals 142, 110326, 2021 | 10 | 2021 |
Concept drift detection on social network data using cross-recurrence quantification analysis RF de Mello, RA Rios, PA Pagliosa, CS Lopes Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (8), 2018 | 9 | 2018 |
Testing for linear and nonlinear Gaussian processes in nonstationary time series RA Rios, M Small, RF de Mello International Journal of Bifurcation and Chaos 25 (01), 1550013, 2015 | 9 | 2015 |