Kiyoumars Roushangar - Associate Professor, Department of Civil Engineering, University of Tabriz, Tabriz, Iran,
Roghayeh Ghasempour - M.Sc student, Department of Civil Engineering, University of Tabriz, Tabriz, Iran,
Hassan sani - Master Graduated of Tabriz University, Department of Civil Engineering, Hydraulic Structures
Farhad Alizadeh Afshar - M.Sc ,Civil Engineering

Insufficient water height above a pipe intake (submergence) may lead to strong vortices formation and air entrainment. Numerous models for predicting critical submergence have been developed over time. Nevertheless, due to the complexity of vortex formation near the intake, the predictive accuracy of these models is often questionable. In current study Artificial Intelligence Techniques were applied to predicting of critical submergence of horizontal intakes in open channel flows. The SVM and ANFIS approaches were compared with the classical models. The obtained results revealed that Artificial Intelligence Techniques approach is so accurate in predicting critical submergence

ANFIS, SVM, critical submergence, intakes