the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A multi-service data management platform for scientific oceanographic products
Alessandro D'Anca
Laura Conte
Paola Nassisi
Cosimo Palazzo
Rita Lecci
Sergio Cretì
Marco Mancini
Alessandra Nuzzo
Maria Mirto
Gianandrea Mannarini
Giovanni Coppini
Sandro Fiore
Giovanni Aloisio
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Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
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To reduce the consequences of landslides due to rainfall, such as of life and economic losses, and disruption of order of our daily living; this study describes the process of building a machine learning model which can help to estimate the volume of landslides material that can occur in a particular region taking into account of antecedent rainfall, soil characteristics, type of vegetation etc. The findings can be useful for land use, infrastructure design and rainfall disaster management.