| Big data and industrial Internet of Things for the maritime industry in Northwestern Norway H Wang, OL Osen, G Li, W Li, HN Dai, W Zeng TENCON 2015-2015 IEEE Region 10 Conference, 1-5, 2015 | 162 | 2015 |
| Fault detection with LSTM-based variational autoencoder for maritime components P Han, AL Ellefsen, G Li, FT Holmeset, H Zhang IEEE Sensors Journal 21 (19), 21903-21912, 2021 | 92 | 2021 |
| A hybrid approach to motion prediction for ship docking—Integration of a neural network model into the ship dynamic model R Skulstad, G Li, TI Fossen, B Vik, H Zhang IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2020 | 88 | 2020 |
| Neural-network-based modelling and analysis for time series prediction of ship motion G Li, B Kawan, H Wang, H Zhang Ship technology research 64 (1), 30-39, 2017 | 82 | 2017 |
| A novel densely connected convolutional neural network for sea-state estimation using ship motion data X Cheng, G Li, AL Ellefsen, S Chen, HP Hildre, H Zhang IEEE Transactions on Instrumentation and Measurement 69 (9), 5984-5993, 2020 | 76 | 2020 |
| An efficient neural-network based approach to automatic ship docking Y Shuai, G Li, X Cheng, R Skulstad, J Xu, H Liu, H Zhang Ocean Engineering 191, 106514, 2019 | 58 | 2019 |
| Incorporating approximate dynamics into data-driven calibrator: A representative model for ship maneuvering prediction T Wang, G Li, LI Hatledal, R Skulstad, V Æsøy, H Zhang IEEE Transactions on Industrial Informatics 18 (3), 1781-1789, 2021 | 56 | 2021 |
| Data-driven uncertainty and sensitivity analysis for ship motion modeling in offshore operations X Cheng, G Li, R Skulstad, P Major, S Chen, HP Hildre, H Zhang Ocean Engineering 179, 261-272, 2019 | 56 | 2019 |
| Temporal attention convolutional neural network for estimation of icing probability on wind turbine blades X Cheng, F Shi, M Zhao, G Li, H Zhang, S Chen IEEE Transactions on Industrial Electronics 69 (6), 6371-6380, 2021 | 54 | 2021 |
| Fault prognostics using LSTM networks: application to marine diesel engine P Han, AL Ellefsen, G Li, V Æsøy, H Zhang IEEE Sensors Journal 21 (22), 25986-25994, 2021 | 51 | 2021 |
| The use of a data-driven digital twin of a smart city: A case study of ålesund, norway P Major, G Li, HP Hildre, H Zhang IEEE Instrumentation & Measurement Magazine 24 (7), 39-49, 2021 | 50 | 2021 |
| Dead reckoning of dynamically positioned ships: Using an efficient recurrent neural network R Skulstad, G Li, TI Fossen, B Vik, H Zhang IEEE Robotics & Automation Magazine 26 (3), 39-51, 2019 | 49 | 2019 |
| From natural complexity to biomimetic simplification: The realization of bionic fish inspired by the cownose ray Y Cai, S Bi, G Li, HP Hildre, H Zhang IEEE Robotics & Automation Magazine 26 (3), 27-38, 2018 | 47 | 2018 |
| A digital twin of the research vessel gunnerus for lifecycle services: Outlining key technologies H Zhang, G Li, LI Hatledal, Y Chu, A Ellefsen, P Han, P Major, R Skulstad, ... IEEE Robotics & Automation Magazine 30 (3), 6-19, 2022 | 44 | 2022 |
| Parameter identification of ship manoeuvring model under disturbance using support vector machine method T Wang, G Li, B Wu, V Æsøy, H Zhang Ships and Offshore Structures 16 (sup1), 13-21, 2021 | 44 | 2021 |
| Locomotion control of a biomimetic robotic fish based on closed loop sensory feedback CPG model D Korkmaz, G Ozmen Koca, G Li, C Bal, M Ay, ZH Akpolat Journal of Marine Engineering & Technology 20 (2), 125-137, 2021 | 43 | 2021 |
| Toward time-optimal trajectory planning for autonomous ship maneuvering in close-range encounters G Li, HP Hildre, H Zhang IEEE Journal of Oceanic Engineering 45 (4), 1219-1234, 2019 | 41 | 2019 |
| A deep learning approach to detect and isolate thruster failures for dynamically positioned vessels using motion data P Han, G Li, R Skulstad, S Skjong, H Zhang IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2020 | 38 | 2020 |
| Modeling and analysis of motion data from dynamically positioned vessels for sea state estimation X Cheng, G Li, R Skulstad, S Chen, HP Hildre, H Zhang 2019 International Conference on Robotics and Automation (ICRA), 6644-6650, 2019 | 38 | 2019 |
| Co-simulation as a fundamental technology for twin ships LI Hatledal, R Skulstad, G Li, A Styve, H Zhang Institutt for teknisk kybernetikk, NTNU, 2020 | 35 | 2020 |
Houxiang ZhangProfessor, Intelligent Systems Lab, Norwegian University of Science and TechnologyVerified email at ntnu.no