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Economía de la tierra y la energía(1)
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Comparison of Machine Learning Techniques Powering Flood Early Warning Systems. Application to a catchment located in the Tropical Andes of Ecuador.
OtherAbstract: Flood Early Warning Systems have globally become an effective tool to mitigate the adverse effects oPalabras claves:Autores:Johanna Orellana-Alvear, Rolando Enrique Célleri AlvearFuentes:googleCalibration of X-band radar for extreme events in a spatially complex precipitation region in north peru: Machine learning vs. empirical approach
ArticleAbstract: Cost-efficient single-polarized X-band radars are a feasible alternative due to their high sensitiviPalabras claves:extreme events, Machine learning, Quantitative precipitation estimate, random forest, Tropical desert, Tropical mountains, weather radarAutores:Johanna Orellana-Alvear, Macalupu S., Nolasco P., Rodriguez R., Rollenbeck R.Fuentes:googlescopusOptimization of X-band radar rainfall retrieval in the southern Andes of Ecuador using a random forest model
ArticleAbstract: Despite many efforts of the radar community, quantitative precipitation estimation (QPE) from weathePalabras claves:Andes, MACHINE-LEARNING, Mountain region, Radar, rainfall retrieval, X-bandAutores:Bendix J., Johanna Orellana-Alvear, Rolando Enrique Célleri Alvear, Rollenbeck R.Fuentes:googlescopusLong short-term memory networks for real-time runoff forecasting using remotely sensed data
OtherAbstract: Current efforts on Deep Learning-based modeling are being put for solving real world problems with cPalabras claves:Autores:Johanna Orellana-AlvearFuentes:googleShort-term Extreme Flow Forecasting in an Tropical Andean Mountain Catchment—Development of a Step-Wise Methodology Based on the Random Forest Algorithm.
OtherAbstract: Flash-flood and drought forecasting has emerged worldwide due to the catastrophic socio-economical iPalabras claves:Autores:Johanna Orellana-Alvear, Rolando Enrique Célleri AlvearFuentes:google