0000000000347948

AUTHOR

João Leal

showing 4 related works from this author

Prediction of compound channel secondary flows using anisotropic turbulence models

2014

PhysicsAnisotropic turbulenceK-epsilon turbulence modelK-omega turbulence modelMechanicsCommunication channel
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A practical methodology to perform global sensitivity analysis for 2D hydrodynamic computationally intensive simulations

2021

Sensitivity analysis is a commonly used technique in hydrological modeling for different purposes, including identifying the influential parameters and ranking them. This paper proposes a simplified sensitivity analysis approach by applying the Taguchi design and the ANOVA technique to 2D hydrodynamic flood simulations, which are computationally intensive. This approach offers an effective and practical way to rank the influencing parameters, quantify the contribution of each parameter to the variability of the outputs, and investigate the possible interaction between the input parameters. A number of 2D flood simulations have been carried out using the proposed combinations by Taguchi (L27…

TC401-506Physical geographyComputer sciencetaguchi designcomputer.software_genreGB3-5030River lake and water-supply engineering (General)VDP::Teknologi: 500Global sensitivity analysisglobal sensitivity analysisData mininganovacomputer2d hydrodynamic flood modelingWater Science and TechnologyHydrology Research
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Downscaling and improving the wind forecasts from NWP for wind energy applications using support vector regression

2020

Abstract The stochastic nature of wind poses challenges in the large scale integration of wind energy with the grid. Wind characteristics at a site may significantly vary with time. which will be reflected on the wind power production. Understanding and managing such variations could be challenging for wind farm owners. energy traders and grid operators. In this work. we propose models based on support vector regression (SVR) to downscale the speed and direction of wind at a specific site using both historical observed measurements and numerical weather predictions (NWP). Several meteorological variables. considered to have potential influence on the wind. were used in the feature selection…

Support vector machineHistoryWind powerMeteorologyVDP::Matematikk og Naturvitenskap: 400::Fysikk: 430business.industryEnvironmental sciencebusinessComputer Science ApplicationsEducationDownscaling
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Emulation of 2D Hydrodynamic Flood Simulations at Catchment Scale Using ANN and SVR

2021

Two-dimensional (2D) hydrodynamic models are one of the most widely used tools for flood modeling practices and risk estimation. The 2D models provide accurate results

Computer scienceProcess (engineering)Geography Planning and DevelopmentAquatic ScienceMachine learningcomputer.software_genreBiochemistrysupport vector regressionTD201-500Uncertainty analysisWater Science and TechnologyEmulationArtificial neural networkFlood mythWater supply for domestic and industrial purposesbusiness.industryDimensionality reductionHydraulic engineeringSupport vector machineemulatorsVDP::Teknologi: 500Sample size determinationerror structureArtificial intelligencetraining set sizebusinessTC1-978computerartificial neural networkWater
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