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Application Of Machine Learning Techniques To Forecast Harmful Algal Blooms In Gulf Of Mexico, Bala Tripura Sundari Yerrapothu
Application Of Machine Learning Techniques To Forecast Harmful Algal Blooms In Gulf Of Mexico, Bala Tripura Sundari Yerrapothu
Master's Theses
The Harmful Algal Blooms (HABs) forecast is crucial for the mitigation of health hazards and to inform actions for the protection of ecosystems and fisheries in the Gulf of Mexico (GoM). For the sake of simplicity of our application we assume ocean color satellite imagery from the National Oceanic and Atmospheric Administration as a proxy for HABs.
In this study we use a deep neural network trained on the 2-Dimensional time series proxy data to provide a forecast of the HABs’ manifestations in the GoM.Our approach analyzes between both spatial and temporal features simultaneously. In addition, the network also helps …