Items where Author is "Jiao, H"

Article

Jiao, H ORCID: 0000-0002-2108-0885, Gong, J ORCID: 0009-0007-6450-7109, Li, H ORCID: 0000-0002-4293-4763, Lam, JSL ORCID: 0000-0001-7920-2665, Shu, Y ORCID: 0009-0001-2529-1516, Wang, J ORCID: 0000-0003-4646-9106 and Yang, Z ORCID: 0000-0003-1385-493X (2025) LLM4STP: A large language model-driven multi-feature fusion method for ship trajectory prediction. Transportation Research Part E: Logistics and Transportation Review, 207. ISSN 1366-5545

Jiao, H, Li, H ORCID: 0000-0002-4293-4763, Lam, JSL, Gao, X and Yang, Z ORCID: 0000-0003-1385-493X (2025) Multi-factor influence-based ship trajectory prediction analysis via deep learning. Journal of Marine Engineering and Technology. pp. 1-19. ISSN 2046-4177

Li, H ORCID: 0000-0002-4293-4763, Xing, W, Jiao, H, Yuen, KF, Gao, R, Li, Y, Matthews, C ORCID: 0000-0002-4126-6484 and Yang, Z ORCID: 0000-0003-1385-493X (2024) Bi-directional information fusion-driven deep network for ship trajectory prediction in intelligent transportation systems. Transportation Research Part E: Logistics and Transportation Review, 192. ISSN 1366-5545

Li, H ORCID: 0000-0002-4293-4763, Xing, W, Jiao, H, Yang, Z ORCID: 0000-0003-1385-493X and Li, Y (2023) Deep bi-directional information-empowered ship trajectory prediction for maritime autonomous surface ships. Transportation Research Part E: Logistics and Transportation Review, 181. ISSN 1366-5545

Li, H ORCID: 0000-0002-4293-4763, Jiao, H and Yang, Z ORCID: 0000-0003-1385-493X (2023) Ship trajectory prediction based on machine learning and deep learning: A systematic review and methods analysis. Engineering Applications of Artificial Intelligence, 126. ISSN 0952-1976

Li, H ORCID: 0000-0002-4293-4763, Jiao, H and Yang, Z ORCID: 0000-0003-1385-493X (2023) AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods. Transportation Research Part E: Logistics and Transportation Review, 175. p. 103152. ISSN 1366-5545