| Prediction of short-term wind and wave conditions for marine operations using a multi-step-ahead decomposition-ANFIS model and quantification of its uncertainty M Wu, C Stefanakos, Z Gao, S Haver Ocean Engineering 188, 106300, 2019 | 35 | 2019 |
| Multi-step-ahead forecasting of wave conditions based on a physics-based machine learning (PBML) model for marine operations M Wu, C Stefanakos, Z Gao Journal of Marine Science and Engineering 8 (12), 992, 2020 | 31 | 2020 |
| The cross-over mechanisms of integral buckle arrestors for offshore pipelines J Yu, J Duan, Z Sun, Y Yu, M Wu Applied Ocean Research 67, 236-247, 2017 | 20 | 2017 |
| Methodology for developing a response-based correction factor (alpha-factor) for allowable sea state assessment of marine operations considering weather forecast uncertainty M Wu, Z Gao Marine Structures 79, 103050, 2021 | 10 | 2021 |
| Research progress of buckling propagation experiment of deep-water pipelines J Yu, M Wu, Z Sun, J Duan Transactions of Tianjin University 22 (4), 285-293, 2016 | 7 | 2016 |
| Assessment of allowable sea states for offshore wind turbine blade installation using time-domain numerical models and considering weather forecast uncertainty M Wu, Z Gao, Y Zhao Ocean Engineering 260, 111801, 2022 | 3 | 2022 |
| Comparison of machine-learning methods for multi-step ahead prediction of wave and wind conditions M Wu, Z Gao, C Stefanakos, S Haver ITISE 2019. Proceedings of papers. Vol 2, 2019 | 1 | 2019 |
| Prediction of short-term wind and wave conditions using Adaptive Network-based Fuzzy Inference System (ANFIS) for marine operations M Wu, C Stefanakos, Z Gao Advances in Renewable Energies Offshore: Proceedings of the 3rd …, 2018 | | 2018 |
