Juniper Publishers| Civil Engineering Journal


Comparison between Three Soft Computing Methods in Estimating Shear Force Carried by Walls in Rough Rectangular Channels Drainage of Flexible Pavement under Laboratory Wheel Track Test




Authored by Hossein Bonakdari
Estimation of shear stress is an important subject in hydraulic engineering, since it affects the flow structure directly. In this study, Support Vector Machine (SVM), Genetic Algorithm Artificial neural network (GAA) as a hybrid method of Artificial Neural Network (ANN)-modified Ge–netic Algorithm (GA) and Genetic Programming (GP) models was used and compared for predicting the percentage of shear force carried by walls (%SFw) in a rectangular channel with rough boundaries.

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