Multilayer Fusion Recurrent Neural Network for Sea Surface Height Anomaly Field Prediction
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DOI: 10.1109/tgrs.2021.3126460
Abstract: Sea surface height anomaly (SSHA) is vitally important for climate and marine ecosystems. This article develops a multilayer fusion recurrent neural network (MLFrnn) to achieve an accurate and holistic prediction of the SSHA field, given… read more here.
Keywords: sea surface; prediction; multilayer fusion; surface height ... See more keywords