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The 3DNet-Catch hydrologic model: Development and evaluation
(Elsevier B.V., 2019)
Hydrologic models are important for effective water resources management. They vary in complexity from parsimonious, spatially lumped, to physically-based, fully distributed models, which are generally expected to outperform ...
The 3DNet-Catch hydrologic model: Development and evaluation
(Elsevier B.V., 2019)
Hydrologic models are important for effective water resources management. They vary in complexity from parsimonious, spatially lumped, to physically-based, fully distributed models, which are generally expected to outperform ...
Transfer learning approach based on satellite image time series for the crop classification problem
(Springer, 2023)
This paper presents a transfer learning approach to the crop classification problem based on time series of images from the Sentinel-2 dataset labeled for two regions: Brittany (France) and Vojvodina (Serbia). During ...
Research in computing‑intensive simulations for nature‑oriented civil‑engineering and related scientific fields, using machine learning and big data: an overview of open problems
(Springer, 2023)
This article presents a taxonomy and represents a repository of open problems in computing for numerically and logically intensive problems in a number of disciplines that have to synergize for the best performance of ...
Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains
(Springer, 2023)
This article describes a teaching strategy that synergizes computing and management, aimed at the running of complex projects in industry and academia, in the areas of civil engineering, physics, geosciences, and a number ...