Prediction of Discharge Coefficient for Ogee Spillway with Curve Axis UsingSupport Vector Machine by Comparison with Adaptive Neuro Fuzzy Inference System

Three-dimensional pattern of flow on ogee spillway and unlimited geometric parameters changing like a change in crest shape, or modification of the approach channel owing to positional geometric qualities may change the flow characteristics on the one hand and the limited information available about hydraulic ogee spillway with curve axis on the other hand, as a major challenge, has led to the use of meta-model systems and data oriented used by researchers. In current study Artificial Intelligence Techniques (Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM)) were applied to predict the discharge coefficient of the ogee spillway with curve axis and compared to experimental data. For this purpose, the experimental data of the ogee spillway model with varying training wall convergence angles, 0