Prediction of Scour at a Side-Weir with GEP, ANN and Regression Models
作者： Fevzi Onen
DOI: 10.1007/S13369-014-1244-Y
关键词:
摘要: Side-weir is known as a lateral intake structure, which widely used in irrigation, land drainage, and urban sewerage system by flow diversion device. Local scour in- /volves the removal of material around piers, abutments, side- weir, spurs, embankments. Clear-water depth based on four dimensional parameters: approach velocity (V1/Vc), water head ratio (h1 − p)/ h1, side-weir length (L/b) sediment size (d50/ p). The equilibrium increases increase dimensionless para- meters velocity, ratio, size. This study presents artificial neural network (ANN) gene expression programming (GEP) models, an algorithm genetic algorithms programming, for prediction clear-water at side-weir. explicit formulations GEP models are developed. GEP-based formulation ANN compared with experimental results, mul- tiple linear/nonlinear regressions (MLR/MNLR). per- formance found slightly more influential than MNLR predicting
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