Multiresolution wavelet-ANN model for significant wave height forecasting.
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Hybrid wavelet artificial neural network (WLNN) has been applied in the present study to forecast significant wave heights (Hs). Here Discrete Wavelet Transformation is used to preprocess the time series data (Hs) prior to Artificial Neural Network (ANN) modeling. The transformed output data are used as inputs to ANN models. Various decomposition levels have been tried for a db3 wavelet to obtain optimal results. It is found that the performance of hybrid WLNN is better than that of ANN when lead time increased considering various performance indices
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