Advancing estuarine box modeling: A novel hybrid machine learning and physics-based approach
2024, Environmental Modelling and Software, Volume 183 - Article number 106223, doi: 10.1016/j.envsoft.2024.106223
Filtering by author: De Lorenzis Alessandro
Enhancing estuary salinity prediction: A Machine Learning and Deep Learning based approach
Saccotelli L., Verri G., De Lorenzis A., Cherubini C.; Caccioppoli R., Coppini G., Maglietta R.
2024, Applied Computing and Geosciences, Volume 23 - Article number 100173, doi: 10.1016/j.acags.2024.100173
Climate projections of the Adriatic Sea: role of river release
Verri G., Furnari L.; Gunduz M., Senatore A.; Santos Da Costa V. , De Lorenzis A., Fedele G., Manco I., Mentaschi L.; Clementi E., Coppini G., Mercogliano P.
2024, Frontiers in Climate, doi: 10.3389/fclim.2024.1368413
Estuary salinity prediction using a Support Vector Machine based approach: a case study of the Po di Goro estuary
Saccotelli L., Verri G., De Lorenzis A., Caccioppoli R., Cherubini C.; Dimauro G.; Coppini G., Maglietta R.
2023, 2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters, MetroSea 2023 - Proceedings, Pages 294 - 298 | 2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters, MetroSea 2023 | La Valletta | 4 October 2023through 6 October 2023 | Code 194563, doi: 10.1109/MetroSea58055.2023.10317103