13 citations as recorded by crossref.

1. A Review of Application of Machine Learning in Storm Surge Problems Y. Qin et al. 10.3390/jmse11091729
2. Convolutional Neural Network and Optical Flow for the Assessment of Wave and Tide Parameters from Video Analysis (LEUCOTEA): An Innovative Tool for Coastal Monitoring G. Scardino et al. 10.3390/rs14132994
3. HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic M. Rus et al. 10.5194/gmd-16-271-2023
4. Forecasting of absolute dynamic topography using deep learning algorithm with application to the Baltic Sea S. Rajabi-Kiasari et al. 10.1016/j.cageo.2023.105406
5. Coastal sea level monitoring in the Mediterranean and Black seas B. Pérez Gómez et al. 10.5194/os-18-997-2022
6. DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin P. Mlakar et al. 10.5194/gmd-17-4705-2024
7. Predicting Sea Level Rise Using Artificial Intelligence: A Review N. Bahari et al. 10.1007/s11831-023-09934-9
8. A deep-learning model for rapid spatiotemporal prediction of coastal water levels A. Shahabi & N. Tahvildari 10.1016/j.coastaleng.2024.104504
9. Coastal Flood Risk Assessment: An Approach to Accurately Map Flooding through National Registry-Reported Events E. Kralj et al. 10.3390/jmse11122290
10. Ensemble Neural Networks for the Development of Storm Surge Flood Modeling: A Comprehensive Review S. Nezhad et al. 10.3390/jmse11112154
11. Prepletanje umetne inteligence in fizike pri napovedovanju obalnih poplav M. Ličer et al. 10.3986/alternator.2021.35
12. A novel deep learning approach for typhoon-induced storm surge modeling through efficient emulation of wind and pressure fields I. Mulia et al. 10.1038/s41598-023-35093-9
13. Modeling of Direct Economic Losses of Storm Surge Disasters Based on a Novel Hybrid Forecasting System H. Guo et al. 10.3389/fmars.2021.804541