Work

Machine Learning Models for Monitoring Salinity in River Estuaries: A Case Study of the Po River

Year: 2024

Type: conference-paper

Source: IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)

DOI: 10.1109/metrosea62823.2024.10765727

Authors: Leonardo Saccotelli, Giorgia Verri, Alessandro De Lorenzis, Carla Cherubini, Giovanni Dimauro, Giovanni Coppini, Rosalia Maglietta

Institutions: CMCC Foundation - Euro-Mediterranean Center on Climate Change, University of Bari Aldo Moro

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: closed

OpenAlex ID: W4404955525

FWCI: 1.058

Cites: 33

Cited by: 1

Related to: 10