کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6784467 | 1432332 | 2018 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An expert system for predicting shear stress distribution in circular open channels using gene expression programming
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
The shear stress distribution in circular channels was modeled in this study using gene expression programming (GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and testing stages. The effect of input variables on GEP modeling was studied and 15 different GEP models with individual, binary, ternary, and quaternary input combinations were investigated. The sensitivity analysis results demonstrate that dimensionless parameter y/P, where y is the transverse coordinate, and P is the wetted perimeter, is the most influential parameter with regard to the shear stress distribution in circular channels. GEP model 10, with the parameter y/P and Reynolds number (Re) as inputs, outperformed the other GEP models, with a coefficient of determination of 0.7814 for the testing data set. An equation was derived from the best GEP model and its results were compared with an artificial neural network (ANN) model and an equation based on the Shannon entropy proposed by other researchers. The GEP model, with an average RMSE of 0.0301, exhibits superior performance over the Shannon entropy-based equation, with an average RMSE of 0.1049, and the ANN model, with an average RMSE of 0.2815 for all flow depths.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Water Science and Engineering - Volume 11, Issue 2, April 2018, Pages 167-176
Journal: Water Science and Engineering - Volume 11, Issue 2, April 2018, Pages 167-176
نویسندگان
Zohreh Sheikh Khozani, Hossein Bonakdari, Isa Ebtehaj,