Alam, Md Mahbub 
; Soares, Amilcar ; Rodrigues Junior, José Fernando ; Spadon, Gabriel
Fonte: Proceedings. Nome do evento: International Symposium on Spatial and Temporal Data - SSTD. Unidade: ICMC
Assuntos: REDES NEURAIS, NAVEGAÇÃO MARÍTIMA
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ALAM, Md Mahbub et al. Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences. 2025, Anais.. New York: ACM, 2025. Disponível em: https://doi.org/10.1145/3748777.3748779. Acesso em: 12 nov. 2025.APA
Alam, M. M., Soares, A., Rodrigues Junior, J. F., & Spadon, G. (2025). Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences. In Proceedings. New York: ACM. doi:10.1145/3748777.3748779NLM
Alam MM, Soares A, Rodrigues Junior JF, Spadon G. Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences [Internet]. Proceedings. 2025 ;[citado 2025 nov. 12 ] Available from: https://doi.org/10.1145/3748777.3748779Vancouver
Alam MM, Soares A, Rodrigues Junior JF, Spadon G. Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences [Internet]. Proceedings. 2025 ;[citado 2025 nov. 12 ] Available from: https://doi.org/10.1145/3748777.3748779
