| Adaptively constrained dynamic time warping for time series classification and clustering H Li, J Liu, Z Yang, RW Liu, K Wu, Y Wan Information Sciences 534, 97-116, 2020 | 189 | 2020 |
| A dimensionality reduction-based multi-step clustering method for robust vessel trajectory analysis H Li, J Liu, RW Liu, N Xiong, K Wu, T Kim Sensors 17 (8), 1792, 2017 | 189 | 2017 |
| Spatio-temporal vessel trajectory clustering based on data mapping and density H Li, J Liu, K Wu, Z Yang, RW Liu, N Xiong IEEE Access 6, 58939-58954, 2018 | 158 | 2018 |
| Data-driven Bayesian network for risk analysis of global maritime accidents H Li, X Ren, Z Yang Reliability Engineering & System Safety 230, 108938, 2023 | 132 | 2023 |
| AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods H Li, H Jiao, Z Yang Transportation Research Part E: Logistics and Transportation Review 175, 103152, 2023 | 90 | 2023 |
| Adaptive douglas-peucker algorithm with automatic thresholding for AIS-based vessel trajectory compression J Liu, H Li, Z Yang, K Wu, Y Liu, RW Liu IEEE Access 7, 150677-150692, 2019 | 84 | 2019 |
| Fine-grained vessel traffic flow prediction with a spatio-temporal multigraph convolutional network M Liang, RW Liu, Y Zhan, H Li, F Zhu, FY Wang IEEE Transactions on Intelligent Transportation Systems 23 (12), 23694-23707, 2022 | 78 | 2022 |
| Unsupervised hierarchical methodology of maritime traffic pattern extraction for knowledge discovery H Li, JSL Lam, Z Yang, J Liu, RW Liu, M Liang, Y Li Transportation Research Part C: Emerging Technologies 143, 103856, 2022 | 67 | 2022 |
| Incorporation of AIS data-based machine learning into unsupervised route planning for maritime autonomous surface ships H Li, Z Yang Transportation Research Part E: Logistics and Transportation Review 176, 103171, 2023 | 65 | 2023 |
| Ship trajectory prediction based on machine learning and deep learning: A systematic review and methods analysis H Li, H Jiao, Z Yang Engineering Applications of Artificial Intelligence 126, 107062, 2023 | 55 | 2023 |
| Fusion with Layered Features of LBP and HOG for Face Recognition HL Y. Wan 计算机辅助设计与图形学学报 27 (4), 640-650, 2015 | 52* | 2015 |
| A data-driven risk model for maritime casualty analysis: A global perspective K Zhou, W Xing, J Wang, H Li, Z Yang Reliability Engineering & System Safety 244, 109925, 2024 | 36 | 2024 |
| PCA-based hierarchical clustering of AIS trajectories with automatic extraction of clusters J Cao, M Liang, Y Li, J Chen, H Li, RW Liu, J Liu 2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA), 448-452, 2018 | 33 | 2018 |
| Deep bi-directional information-empowered ship trajectory prediction for maritime autonomous surface ships H Li, W Xing, H Jiao, Z Yang, Y Li Transportation Research Part E: Logistics and Transportation Review 181, 103367, 2024 | 31 | 2024 |
| Multi-scale collision risk estimation for maritime traffic in complex port waters X Xin, K Liu, S Loughney, J Wang, H Li, N Ekere, Z Yang Reliability Engineering & System Safety 240, 109554, 2023 | 31 | 2023 |
| Graph-based ship traffic partitioning for intelligent maritime surveillance in complex port waters X Xin, K Liu, S Loughney, J Wang, H Li, Z Yang Expert Systems with Applications 231, 120825, 2023 | 27 | 2023 |
| Applications, evolutions, and challenges of drones in maritime transport J Wang, K Zhou, W Xing, H Li, Z Yang Journal of Marine Science and Engineering 11 (11), 2056, 2023 | 27 | 2023 |
| Maritime traffic partitioning: An adaptive semi-supervised spectral regularization approach for leveraging multi-graph evolutionary traffic interactions X Xin, K Liu, H Li, Z Yang Transportation Research Part C: Emerging Technologies 164, 104670, 2024 | 25 | 2024 |
| Prediction of the severity of marine accidents using improved machine learning Y Feng, X Wang, Q Chen, Z Yang, J Wang, H Li, G Xia, Z Liu Transportation Research Part E: Logistics and Transportation Review 188, 103647, 2024 | 24 | 2024 |
| Dynamic evolution of maritime accidents: Comparative analysis through data-driven Bayesian Networks H Li, K Zhou, C Zhang, M Bashir, Z Yang Ocean Engineering 303, 117736, 2024 | 21 | 2024 |
Zaili YangProfessor, Liverpool John Moores UniversityGeverifieerd e-mailadres voor ljmu.ac.uk
