GMDH to predict scour depth around a pier in cohesive soils

This study presents new application of group method of data handling (GMDH) to predict scour depth around a vertical pier in cohesive soils. Quadratic polynomial was used to develop GMDH network. Back propagation algorithm has been utilized to adjust weighting coefficients of GMDH polynomial thorough trial and error method. Parameters such as initial water content, shear strength, compaction of cohesive bed materials, clay content of cohesive soils, and flow conditions are main factors affecting cohesive scour. Performances of the GMDH network were compared with those obtained using several traditional equations. The results indicated that the proposed GMDH-BP has produced quite better scour depth prediction than those obtained using traditional equations. To assign the most significant parameter on scour process in cohesive soils, sensitivity analysis was performed for the GMDH-BP network and the results showed that clay percentage was the most effective parameter on scour depth. The error parameter for three classes of IWC and Cp showed that the GMDH-BP model yielded better scour prediction in ranges of IWC = 36.3–42.28% and Cp = 35–100%. In particular application, the GMDH network was proved very successful compared to traditional equations. The GMDH network was presented as a new soft computing technique for the scour depth prediction around bridge pier in cohesive bed materials.

▸ Quadratic polynomial was used to develop GMDH network. ▸ The GMDH network provided significantly accurate outcomes compared to ones of traditional equations. ▸ Debnath and Chaudhuri equation provided quite better scour depth than other traditional equations. ▸ Results of sensitivity analysis showed that clay percent was the most effective parameter.