| A review of sensing technologies for non-destructive evaluation of structural composite materials R Gupta, D Mitchell, J Blanche, S Harper, W Tang, K Pancholi, L Baines, ... Journal of Composites Science 5 (12), 319, 2021 | 42 | 2021 |
| A review: Challenges and opportunities for artificial intelligence and robotics in the offshore wind sector D Mitchell, J Blanche, S Harper, T Lim, R Gupta, O Zaki, W Tang, V Robu, ... Energy and AI 8, 100146, 2022 | 35 | 2022 |
| Prognostics and health management for the optimization of marine hybrid energy systems W Tang, D Roman, R Dickie, V Robu, D Flynn Energies 13 (18), 4676, 2020 | 27 | 2020 |
| Real user evaluation of a POMDP spoken dialogue system using automatic belief compression PA Crook, S Keizer, Z Wang, W Tang, O Lemon Computer Speech & Language 28 (4), 873-887, 2014 | 19 | 2014 |
| Data analysis of battery storage systems M Andoni, W Tang, V Robu, D Flynn CIRED-Open Access Proceedings Journal 2017 (1), 96-99, 2017 | 16 | 2017 |
| Certification of safe and trusted robotic inspection of assets F Dinmohammadi, V Page, D Flynn, V Robu, M Fisher, C Patchett, ... 2018 Prognostics and System Health Management Conference (PHM-Chongqing …, 2018 | 12 | 2018 |
| The application of machine learning and low frequency sonar for subsea power cable integrity evaluation W Tang, D Flynn, K Brown, R Valentin, X Zhao OCEANS 2019 MTS/IEEE SEATTLE, 1-6, 2019 | 10 | 2019 |
| Accurately forecasting the health of energy system assets W Tang, M Andoni, V Robu, D Flynn 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2018 | 10 | 2018 |
| Optimisation of hybrid energy systems for maritime vessels W Tang, R Dickie, D Roman, V Robu, D Flynn The Journal of Engineering 2019 (17), 4516-4521, 2019 | 8 | 2019 |
| Machine Learning Analysis of Non-Destructive Evaluation Data from Radar Inspection of Wind Turbine Blades W Tang, D Mitchell, J Blanche, R Gupta, D Flynn 2021 IEEE International Conference on Sensing, Diagnostics, Prognostics, and …, 2021 | 7 | 2021 |
| Sensing technologies and artificial intelligence for subsea power cable asset management W Tang, D Flynn, V Robu 2021 IEEE International Conference on Prognostics and Health Management …, 2021 | 7 | 2021 |
| Integrity analysis inspection and lifecycle prediction of subsea power cables W Tang, K Brown, D Flynn, H Pellae 2018 Prognostics and System Health Management Conference (PHM-Chongqing …, 2018 | 7 | 2018 |
| Applying machine learning to predict asset health in hybrid maritime vessels W Tang, D Flynn, V Robu 13th International Conference on Condition Monitoring and Machinery Failure …, 2016 | 6 | 2016 |
| The design of a fusion prognostic model and health management system for subsea power cables W Tang, D Flynn, K Brown, R Valentin, X Zhao OCEANS 2019 MTS/IEEE SEATTLE, 1-6, 2019 | 5 | 2019 |
| PHM of Subsea Cables D Flynn, C Bailey, P Rajaguru, W Tang, C Yin Prognostics and Health Management of Electronics: Fundamentals, Machine …, 2018 | 5 | 2018 |
| Characterisation of composite materials for wind turbines using frequency modulated continuous wave sensing W Tang, J Blanche, D Mitchell, S Harper, D Flynn Journal of Composites Science 7 (2), 75, 2023 | 3 | 2023 |
| On the linear belief compression of POMDPs: A re-examination of current methods Z Wang, PA Crook, W Tang, O Lemon arXiv preprint arXiv:1508.00986, 2015 | 3 | 2015 |
| Optimisation of hybrid energy systems for maritime vessels D Flynn, W Tang, D Roman, R Dickie, V Robu 9th International Conference on Power Electronics, Machines and Drives 2018, 2018 | 2 | 2018 |
| Prognostics and health management of subsea cables D Flynn, C Bailey, P Rajaguru, T Wenshuo, C Yin Wiley-Blackwell, 2019 | 1 | 2019 |
| Subsea Power Cable Health Management Using Machine Learning Analysis of Low-Frequency Wide-Band Sonar Data W Tang, K Brown, D Mitchell, J Blanche, D Flynn Energies 16 (17), 6172, 2023 | | 2023 |
David FlynnProfessor , University of GlasgowПодтвержден адрес электронной почты в домене Glasgow.ac.uk
