Prediction of Ultimate Bearing Capacity of Circularand Square Footings by Neural Network

For ultimate bearing capacity calculation, various Analytical – Experimental methods were proposed by Terzaghi, Mayerhof, Hansen and Vesic and the most comprehensive one in case of no axial load was proposed by Mayerhof. In this article Artificial Neural Network (ANN) is used to predict bearing capacity of circular and square shallow foundations and for this purpose Multi-layer Perceptron (MLP) is utilized. The data usedas the inputs and output of network models were parameters in Mayerhof equation and the bearing capacity calculated from this equation, respectively. Finding the best architecture of model is carried out through making different conditions such as numbers of hidden neurons and activation functions. The result of this work shows high capabilities of this kind of neural network for bearing capacity prediction

Prediction of Ultimate Bearing Capacity of Circularand Square Footings by Neural Network Keywords:

Bearing Capacity , Mayerhof , Artificial Neural Network , MLP