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The effects of COVID-19 on Chinese commuting patterns in early 2020.

, , , , and . GEOINFO, page 317-322. MCTIC/INPE, (2022)

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Séries Temporais Multivariadas Para Previsão de Lentidão de Trânsito: Uma Comparação Entre Prophet e LSTM., , , and . GEOINFO, page 489-494. MCTI/INPE, (2023)Reactive Agent-based Model for Convergence of Autonomous Vehicles to Parallel Formations Heading to Predefined Directions of Motion., and . ICAART (1), page 166-173. SciTePress, (2017)Complex Networks Approach for Dynamical Characterization of Nonlinear Systems., , and . Int. J. Bifurc. Chaos, 29 (13): 1950188:1-1950188:10 (2019)A Decidability-Based Loss Function., , , , , and . IJCNN, page 1-8. IEEE, (2022)Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks., , , and . CoRR, (2020)The effects of COVID-19 on Chinese commuting patterns in early 2020., , , , and . GEOINFO, page 317-322. MCTIC/INPE, (2022)Time Series Forecasting of COVID-19 Cases in Brazil with GNN and Mobility Networks., , , , and . BRACIS (3), volume 14197 of Lecture Notes in Computer Science, page 361-375. Springer, (2023)Correlations Between Epidemiological Time Series Forecasting and Influence Regions of Brazilian Cities., , , , and . GEOINFO, page 340-345. MCTI/INPE, (2023)ShpStreetGraph: From spatial relations of streets to graph representations., , , and . Softw. Impacts, (2024)Synchronization-based symmetric circular formations of mobile agents and the generation of chaotic trajectories., , , and . Commun. Nonlinear Sci. Numer. Simul., (2021)