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Global horizontal and direct normal solar irradiance modeling by the machine learning methods XGBoost and deep neural networks with CNN-LSTM layers: a case study using the GOES-16 satellite imagery

Paulo Alexandre Costa Rocha, Victor Oliveira Santos

2022International journal of energy and environmental engineering40 citationsDOI

Topics & Concepts

Convolutional neural networkMean squared errorBenchmark (surveying)IrradianceArtificial neural networkRenewable energyComputer scienceSatelliteSolar irradianceDeep learningAlgorithmSolar energyArtificial intelligenceEnvironmental scienceRemote sensingMeteorologyMathematicsCartographyEngineeringStatisticsGeographyPhysicsOpticsAerospace engineeringElectrical engineeringSolar Radiation and PhotovoltaicsPhotovoltaic System Optimization TechniquesImpact of Light on Environment and Health
Global horizontal and direct normal solar irradiance modeling by the machine learning methods XGBoost and deep neural networks with CNN-LSTM layers: a case study using the GOES-16 satellite imagery | Litcius