Chapter

Computational Intelligence Techniques in Earth and Environmental Sciences

pp 197-208

Date:

Prediction of Local Scour Depth Downstream of Bed Sills Using Soft Computing Models

  • A. ZahiriAffiliated withWater Engineering Department, Gorgan University of Agricultural Sciences and Natural Resources Email author 
  • , H. Md. AzamathullaAffiliated withREDAC, Universiti Sains Malaysia
  • , Kh. GhorbaniAffiliated withWater Engineering Department, Gorgan University of Agricultural Sciences and Natural Resources

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Abstract

Bed sill local scour is an important issue in environmental and water resources engineering in order to prevent degradation of river bed and save the stability of grade-control structures. This chapter presents genetic algorithms (GA), gene expression programming, and M5 decision tree model as an alternative approaches to predict scour depth downstream of bed sills. Published data were compiled from the literature for the scour depth downstream of sills. The proposed GA approach gives satisfactory results (R 2 = 0.96 and RMSE = 0.442) compared to existing predictors.

Keywords

Grade-control structures Local scour Genetic algorithms M5 tree decision model Gene expression programming