Combining a Fully Connected Neural Network With an Ensemble Kalman Filter to Emulate a Dynamic Model in Data Assimilation
Using neural network technology, dynamic characteristics can be learned from model output or assimilation results to train the model, which has greatly progressed recently.A data-driven data assimilation method is proposed by combining fully connected neural network with ensemble Kalman filter to emulate dynamic models from sparse and noisy observa