المؤلفون: Cruz, Lívia Almada, Coelho da Silva, Ticiana Linhares Coelho, Magalhães, Régis Pires, Melo, Wilken Charles Dantas, Cordeiro, Matheus Gomes, de Macedo, José António Fernandes D., Zeitouni, Karine

المساهمون: Universidade Federal do Ceará = Federal University of Ceará (UFC), Données et algorithmes pour une ville intelligente et durable - DAVID (DAVID), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Horizon 2020 Framework Programme, H2020, This paper is partially supported by the MASTER project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement Nº777695.

المصدر: ISSN: 1424-8220 ; Sensors ; https://hal.science/hal-03837174 ; Sensors, 2022, 22 (19), pp.7475. ⟨10.3390/s22197475⟩.

مصطلحات موضوعية: location prediction, representation learning, sensors trajectory, trajectory embedding, trajectory modeling, trajectory prediction, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing

Relation: info:eu-repo/semantics/altIdentifier/pmid/36236581; hal-03837174; https://hal.science/hal-03837174; https://hal.science/hal-03837174/document; https://hal.science/hal-03837174/file/sensors-22-07475-v2.pdf; PUBMED: 36236581

الاتاحة: https://hal.science/hal-03837174
https://hal.science/hal-03837174/document
https://hal.science/hal-03837174/file/sensors-22-07475-v2.pdf
https://doi.org/10.3390/s22197475