چکیده مقاله
In this investigation, stable width W , depth D and slope S have been estimated using Artificial Neural Network ANN and Support Vector Machine SVM methods The results obtained from these two methods were compared with previous regression formulas of Afzalimehr The proposed models were trained and tested using 85 field data sets The accuracy of the models was evaluated using RMSE1, MAE2, MARE3 and R4 statistical parameters Results show that the SVM with MARE of 0 061, 0 042 and 0 074 was found to be better than ANN with MARE of 0 072, 0 076 and 1 82 and regression based equations with MARE of 4 51, 0 9 and 0 95 for width, depth and slope respectively Generally, the results show that regression equations can not accurately estimate the stable channel geometry due to their high error amounts of RMSE, MAE and MARE So, the application of a new method such as ANN and SVM models is investigated in this paper
کلیدواژهها
نویسندگان
Saba Shaghaghi
M Sc Student, Department of Civil Engineering, Razi University, Kermanshah, Iran,
Hossein Bonakdari
Associate Prof, Department of Civil Engineering, Razi University, Kermanshah, Iran,
Azadeh gholami
Ph D Student, Department of Civil Engineering, Razi University, Kermanshah, Iran,
Isa Ebtehaj
Ph D Student, Department of Civil Engineering, Razi University, Kermanshah, Iran,
شیوه ارجاع
Shaghaghi, Saba and Bonakdari, Hossein and gholami, Azadeh and Ebtehaj, Isa,1394,Application of Artifitial Neural Network (ANN) and Support Vector Machine (SVM) in estimation of stable channel geometry,10th International River Engineering Conference,Ahvaz
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