In this study, group method of data handling (GMDH) based wavelet transform (WT) was developed to forecast significant wave height (SWH) in different lead times. The SWH datasets was collected from a buoy station located in the North Atlantic Ocean. For this purpose, time series of SWH was decomposed into some subseries using WT and then decomposed time series were imported to GMDH model to forecast the SWH. Performance of the wavelet group method of data handling (WGMDH) model was evaluated using index of agreement (Ia), coefficient of efficiency and root mean square error. The analysis proved that the model accuracy is highly depended on the decomposition levels. The results showed that WGMDH model is able to forecast the SWH with a high reliability.
- lead time
- significant wave height
- time series
- wavelet transform
- First received 13 January 2015.
- Accepted in revised form 29 September 2015.
- © IWA Publishing 2015