عنوان مقاله :
Prediction of Ultimate Soil Bearing Capacity for Shallow Strip Foundation on Sandy Soils Using (ANN) Technique
پديد آورندگان :
Esmat, Zainal, Abdul Kareem University of Baghdad - College of Engineering - Department of Civil Engineering, Iraq , Al_Saidi, A amal University of Baghdad - College of Engineering - Department of Civil Engineering, Iraq
چكيده عربي :
Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that using ANN gave a very high correlation factor associated with the results obtained from Terzagih’s equation, besides little computation time needed compared with computation time needed when applying Terzagih’s equation.
چكيده لاتين :
Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that using ANN gave a very high correlation factor associated with the results obtained from Terzagih’s equation, besides little computation time needed compared with computation time needed when applying Terzagih’s equation.
كليدواژه :
Soil Bearing capacity , Artificial Neural Network , shallow foundation.
عنوان نشريه :
جامعه ذي قار