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Prediction of chlorophyll-a as an indicator of harmful algal blooms using deep learning with Bayesian approximation for uncertainty assessment

Ibrahim Busari, Debabrata Sahoo, R.B. Jana

2024Journal of Hydrology31 citationsDOI

Topics & Concepts

Dropout (neural networks)Mean squared errorEnvironmental scienceAlgal bloomSampling (signal processing)Chlorophyll aChlorophyllWater qualityBayesian probabilityComputer scienceStatisticsMachine learningMathematicsArtificial intelligencePhytoplanktonNutrientEcologyChemistryOrganic chemistryBiologyComputer visionBotanyFilter (signal processing)Hydrological Forecasting Using AIWater Quality Monitoring TechnologiesWater Quality Monitoring and Analysis
Prediction of chlorophyll-a as an indicator of harmful algal blooms using deep learning with Bayesian approximation for uncertainty assessment | Litcius