Nonstationary time series transformation methods: An experimental review R Salles, K Belloze, F Porto, PH Gonzalez, E Ogasawara Knowledge-Based Systems 164, 274-291, 2019 | 96 | 2019 |
Estimation of COVID-19 under-reporting in the Brazilian states through SARI B Paixão, L Baroni, M Pedroso, R Salles, L Escobar, C de Sousa, ... New Generation Computing 39, 623-645, 2021 | 31 | 2021 |
Evaluating temporal aggregation for predicting the sea surface temperature of the Atlantic Ocean R Salles, P Mattos, AMD Iorgulescu, E Bezerra, L Lima, E Ogasawara Ecological Informatics 36, 94-105, 2016 | 29 | 2016 |
A framework for benchmarking machine learning methods using linear models for univariate time series prediction R Salles, L Assis, G Guedes, E Bezerra, F Porto, E Ogasawara 2017 International Joint Conference on Neural Networks (IJCNN), 2338-2345, 2017 | 15 | 2017 |
An integrated dataset of malaria notifications in the Legal Amazon L Baroni, M Pedroso, C Barcellos, R Salles, S Salles, B Paixão, ... BMC Research Notes 13, 1-3, 2020 | 10 | 2020 |
Database on the coverage of the “Bolsa-Família” conditioning cash-transfer program: Brazil, 2005 to 2021 L Baroni, RFS Alves, CS Boccolini, R Salles, R Gritz, B Paixão, ... BMC Research Notes 14, 1-3, 2021 | 9 | 2021 |
An analysis of malaria in the Brazilian Legal Amazon using divergent association rules L Baroni, R Salles, S Salles, G Guedes, F Porto, E Bezerra, C Barcellos, ... Journal of Biomedical Informatics 108, 103512, 2020 | 9 | 2020 |
Harbinger: Um framework para integração e análise de métodos de detecção de eventos em séries temporais R Salles, L Escobar, L Baroni, R Zorrilla, A Ziviani, V Kreischer, F Delicato, ... Simpósio Brasileiro de Banco de Dados (SBBD), 73-84, 2020 | 7 | 2020 |
Machine learning approaches to extreme weather events forecast in urban areas: Challenges and initial results F Porto, M Ferro, E Ogasawara, T Moeda, CDT de Barros, AC Silva, ... Supercomputing Frontiers and Innovations 9 (1), 49-73, 2022 | 6 | 2022 |
TSPred: a framework for nonstationary time series prediction R Salles, E Pacitti, E Bezerra, F Porto, E Ogasawara Neurocomputing 467, 197-202, 2022 | 6 | 2022 |
Evaluating Linear Models as a Baseline for Time Series Imputation. R Salles, E Bezerra, J de Abreu Soares, ES Ogasawara SBBD (Short Papers), 63-68, 2015 | 6 | 2015 |
Forward and backward inertial anomaly detector: a novel time series event detection method J Lima, R Salles, F Porto, R Coutinho, P Alpis, L Escobar, E Pacitti, ... 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 5 | 2022 |
TSPred: functions for baseline-based time series prediction RP Salles, E Ogasawara R package version 4, 2015 | 5 | 2015 |
Neonatal mortality rates in Brazilian municipalities: from 1996 to 2017 L Baroni, R Salles, S Salles, M Pedroso, J Lima, I Morais, L Carraro, ... BMC Research Notes 14, 1-3, 2021 | 3 | 2021 |
Evaluating temporal bias in time series event detection methods L Escobar, R Salles, J Lima, C Gea, L Baroni, A Ziviani, P Pires, ... Journal of Information and Data Management 12 (3), 2021 | 3 | 2021 |
Online event detection for sensor data E Ogasawara, R Salles, L Escobar, L Baroni, J Lima, F Porto Proceedings of the Ibero-Latin-American Congress on Computational Methods in …, 2021 | 3 | 2021 |
A Conceptual Vision Toward the Management of Machine Learning Models. DNR da Silva, A Simões, C Cardoso, DEM de Oliveira, JN Rittmeyer, ... ER Forum/Posters/Demos, 15-27, 2019 | 3 | 2019 |
SoftED: Metrics for Soft Evaluation of Time Series Event Detection R Salles, J Lima, R Coutinho, E Pacitti, F Masseglia, R Akbarinia, C Chen, ... arXiv preprint arXiv:2304.00439, 2023 | 2 | 2023 |
Data science platform applied to health in contribution to the brazilian unified health system M Pedroso, R Salles, R Saldanha, VK Almeida, G Souto, B Paixão, ... | 2 | 2023 |
Requirements for an ontology of digital twins C Barros, R Salles, E Ogasawara, G Guizzardi, F Porto CEUR workshop proceedings 2941, 2021 | 2 | 2021 |