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From local to regional compound flood mapping with deep learning and data fusion techniques
ArticleAbstract: Compound flooding (CF), as a result of oceanic, hydrological, meteorological and anthropogenic drivePalabras claves:Compound flood mapping, convolutional neural networks, data fusion, deep learning, hurricanesAutores:Moftakhari H., Moradkhani H., Muñoz D.F., Paul MuñozFuentes:googlescopusFusing Multisource Data to Estimate the Effects of Urbanization, Sea Level Rise, and Hurricane Impacts on Long-Term Wetland Change Dynamics
ArticleAbstract: Wetlands are endangered ecosystems that provide vital habitats for flora and fauna worldwide. They sPalabras claves:data fusion, deep learning, hurricane impacts, mobile bay, Sea level rise, urban development, wetland lossAutores:Alipour A., Moftakhari H., Moradkhani H., Mortazavi B., Muñoz D.F., Paul MuñozFuentes:googlescopusFlood early warning systems using machine learning techniques: The case of the tomebamba catchment at the southern Andes of Ecuador
ArticleAbstract: Worldwide, machine learning (ML) is increasingly being used for developing flood early warning systePalabras claves:Andes, Flood early warning, forecasting, hydrological extremes, Machine learningAutores:Bendix J., Jan Jozef Albert Feyen, Johanna Orellana-Alvear, Paul Muñoz, Rolando Enrique Célleri AlvearFuentes:googlescopusInfluence of random forest hyperparameterization on short-term runoff forecasting in an andean mountain catchment
ArticleAbstract: The Random Forest (RF) algorithm, a decision-tree-based technique, has become a promising approach fPalabras claves:Machine learning, Optimal hyperparameters, random forest, Runoff forecasting, Tropical AndesAutores:Bendix J., Contreras P., Johanna Orellana-Alvear, Paul Muñoz, Rolando Enrique Célleri AlvearFuentes:googlescopus