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THEME D: Numerical and Experimental Methods - Machine Learning
Time:
Wednesday, 05/June/2024:
1:30pm - 3:00pm
Session Chair: Gonçalo Jesus Session Chair: Paulo Diogo
Location:Room 2
Presentations
Oral presentation
Hybrid physically based and machine learning model for streamflow prediction
Sergio Ricardo López-Chacón1, Fernando Salazar1,2, Ernest Bladé2
1International Centre for Numerical Methods in Engineering (CIMNE), 08034 Barcelona, Spain; 2Flumen Institute, Universitat Politècnica de Catalunya (UPC BarcelonaTech)—International Centre for Numerical Methods in Engineering (CIMNE), 08034 Barcelona, Spain
Oral presentation
A Comparative Analysis of Deep Learning Techniques for River Flow Forecasting in Northwest Spain
Juan F. Farfán-Durán, Luis Cea
Universidade da Coruña, Water and Environmental Engineering Group, Center for Technological Innovation in Construction and Civil Engineering (CITEEC), Elviña, 15071 A Coruña, Spain
Oral presentation
Machine Learning Methodologies for Leakage Flow in a Masonry Dam (Santa Fe's dam)
Enrique Bonet, Maria Teresa Yubero, Lluís Sanmiquel, Marc Bascompte
UPC EPSEM, Spain
Oral presentation
Experimental prediction of 1-dimensional riverbed deformation using machine learning along the Mogami river, Japan
Tao Yamamoto, So Kazama
Tohoku University, Japan
Oral presentation
Machine learning-based hydropower turbine designs
Ante Sikirica1, Marta Alvir2, Zoran Čarija2, Lado Kranjčević2
1Center for Advanced Computing and Modelling, University of Rijeka, Croatia; 2Faculty of Engineering, University of Rijeka, Croatia
