26 citations as recorded by crossref.

1. Beach erosion under rising sea‐level modulated by coastal geomorphology and sediment availability on carbonate reef‐fringed island coasts B. Romine et al. 10.1111/sed.12264
2. Detecting Changes in European Shoreline Evolution Trends Using Markov Chains and the Eurosion Database G. Le Cozannet et al. 10.3389/fmars.2020.00326
3. Assessing Po River Deltaic Vulnerability Using Earth Observation and a Bayesian Belief Network Model A. Taramelli et al. 10.3390/w12102830
4. Applicability of parametric beach morphodynamic state classification on embayed beaches C. Loureiro et al. 10.1016/j.margeo.2013.09.005
5. Long-Term Shoreline Change at Kailua, Hawaii, Using Regularized Single Transect T. Anderson et al. 10.2112/JCOASTRES-D-13-00202.1
6. A Bayesian network model for assessments of coastal inundation pathways and probabilities S. Narayan et al. 10.1111/jfr3.12200
7. Application of Bayesian Networks to hindcast barrier island morphodynamics K. Wilson et al. 10.1016/j.coastaleng.2015.04.006
8. A Review of Satellite Remote Sensing Techniques of River Delta Morphology Change D. Munasinghe et al. 10.1007/s41976-021-00044-3
9. Vulnerability of sandy coasts to climate variability D. Idier et al. 10.3354/cr01153
10. The use of genetic programming to develop a predictor of swash excursion on sandy beaches M. Passarella et al. 10.5194/nhess-18-599-2018
11. National evaluation of Chinese coastal erosion to sea level rise using a Bayesian approach Q. Zhan et al. 10.1088/1755-1315/18/1/012136
12. Approaches to evaluate the recent impacts of sea-level rise on shoreline changes G. Le Cozannet et al. 10.1016/j.earscirev.2014.08.005
13. The dynamic effects of sea level rise on low‐gradient coastal landscapes: A review D. Passeri et al. 10.1002/2015EF000298
14. Coastal forecast through coupling of Artificial Intelligence and hydro-morphodynamical modelling P. Kumar & N. Leonardi 10.1080/21664250.2023.2233724
15. Doubling of coastal erosion under rising sea level by mid-century in Hawaii T. Anderson et al. 10.1007/s11069-015-1698-6
16. Determining the Shoreline Retreat Rate of Australia Using Discrete and Hybrid Bayesian Networks Y. Mao et al. 10.1029/2021JF006112
17. Application of Artificial Neural Networks to Predict Beach Nourishment Volume Requirements D. Bujak et al. 10.3390/jmse9080786
18. The Field Geomorphologist in a Time of Artificial Intelligence and Machine Learning C. Houser et al. 10.1080/24694452.2021.1985956
19. A machine-learning hybrid-classification method for stratification of multidecadal beach dynamics V. Rodriguez-Galiano et al. 10.1080/10106049.2022.2110616
20. Gaining insight into regional coastal changes on La Réunion island through a Bayesian data mining approach T. Bulteau et al. 10.1016/j.geomorph.2014.09.002
21. Monitoring Cliff Erosion with LiDAR Surveys and Bayesian Network-based Data Analysis P. Terefenko et al. 10.3390/rs11070843
22. Correlation Between Shoreline Change and Planform Curvature on Wave‐Dominated, Sandy Coasts R. Lauzon et al. 10.1029/2019JF005043
23. A review of machine learning applications to coastal sediment transport and morphodynamics E. Goldstein et al. 10.1016/j.earscirev.2019.04.022
24. Tidal hydrodynamics under future sea level rise and coastal morphology in the Northern Gulf of Mexico D. Passeri et al. 10.1002/2015EF000332
25. Likely and High-End Impacts of Regional Sea-Level Rise on the Shoreline Change of European Sandy Coasts Under a High Greenhouse Gas Emissions Scenario R. Thiéblemont et al. 10.3390/w11122607
26. A Regional Application of Bayesian Modeling for Coastal Erosion and Sand Nourishment Management A. Giardino et al. 10.3390/w11010061