title: Gene-expression programming for flip-bucket spillway scour.
abstract: During the last two decades, researchers have noticed that the use of soft computing techniques as an alternative to conventional statistical methods based on controlled laboratory or field data, gave significantly better results. Gene-expression programming (GEP), which is an extension to genetic programming (GP), has nowadays attracted the attention of researchers in prediction of hydraulic data. This study presents GEP as an alternative tool in the prediction of scour downstream of a flip-bucket spillway. Actual field measurements were used to develop GEP models. The proposed GEP models are compared with the earlier conventional GP results of others (Azamathulla et al. 2008b; RMSE = 2.347, δ = 0.377, R = 0.842) and those of commonly used regression-based formulae. The predictions of GEP models were observed to be in strictly good agreement with measured ones, and quite a bit better than conventional GP and the regression-based formulae. The results are tabulated in terms of statistical error measures (GEP1; RMSE = 1.596, δ = 0.109, R = 0.917) and illustrated via scatter plots.
authors.affiliation: Department of Civil Engineering, University of Gaziantep, Turkey.
authors.forename: Aytac
authors.initials: A
authors.lastname: Guven
authors.forename: H Md
authors.initials: HM
authors.lastname: Azamathulla
mesh_terms: D003198:Computer Simulation; D004738:Engineering; D004784:Environmental Monitoring; D020869:Gene Expression Profiling / Q000379:methods; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D012984:Software; D014872:Water Movements