کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
303670 512750 2012 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The use of neural networks for the prediction of the critical factor of safety of an artificial slope subjected to earthquake forces
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
The use of neural networks for the prediction of the critical factor of safety of an artificial slope subjected to earthquake forces
چکیده انگلیسی

This study deals with the development of Artificial Neural Network (ANN) and Multiple Regression (MR) models for estimating the critical factor of safety (Fs)(Fs) value of a typical artificial slope subjected to earthquake forces. To achieve this, while the geometry of the slope and the properties of the man-made soil are kept constant, the natural subsoil properties, namely, cohesion, internal angle of friction, the bulk unit weight of the layer beneath the ground surface and the seismic coefficient, varied during slope stability analyses. Then, the FsFs values of this slope were calculated using the simplified Bishop method, and the minimum (critical  ) FsFs value for each case was determined and used in the development of the ANN and MR models. The results obtained from the models were compared with those obtained from the calculations. Moreover, several performance indices, such as determination coefficient, variance account for, mean absolute error and root mean square error, were calculated to check the prediction capacity of the models developed. The obtained indices make it clear that the ANN model has shown a higher prediction performance than the MR model.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Scientia Iranica - Volume 19, Issue 2, April 2012, Pages 188–194
نویسندگان
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