Comparison between Three Soft Computing
Methods in Estimating Shear Force Carried by
Walls in Rough Rectangular Channels in Juniper in Civil Engineering Research Journal (CERJ)
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 Genetic 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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