Wave runup prediction using M5′ model tree algorithm

In recent years, soft computing schemes have received increasing attention for solving coastal engineering problems and knowledge extraction from the existing data. In this paper, capabilities of M5′ Decision Tree algorithm are implemented for predicting the wave runup using existing laboratory data. The decision models were established using the surf similarity parameter (ξ), slope angle (cot α), beach permeability factor (Sp), relative wave height (H/h), wave spectrum (Ss) and wave momentum flux (m). 451 laboratory data of the wave runup were utilized for developing wave runup prediction models. The performance of developed models is evaluated with statistical measures. The results demonstrate the strength of M5′ model tree algorithm in predicting the wave runup with high precision. Good agreement exists between the proposed runup formulae and existing empirical relations.