Prediction of wave parameters is necessary for many applications in coastal and offshore engineering. In the literature, several approaches have been proposed to wave predictions classified as empirical based, soft-computing based and numerical based approaches. Recently, soft computing techniques such as Artificial Neural Networks (ANNs) have been used to develop wave prediction models. In this work, the performance of regression trees for prediction of wave parameters was investigated. The data set used in this study comprises of wind and wave data gathered in Caspian Sea. Results of regression trees were compared with those of artificial neural networks. Results indicate that error statistics of regression trees and artificial neural networks were nearly similar. In addition, regression trees need lower run-time.
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