Application of artificial neural network in the forecast the ultimate bearing capacity of shallow foundations

Abstract

ABSTRACT

This paper presents the results of applying an artificial neural network model in determining the load-bearing capacity of shallow foundations. An artificial neural network model has been built and optimized architecture, using genetic algorithms to determine shallow foundation resistance. A dataset consisting of 112 results of shallow foundation load tests with different dimensions is used to train and test the model. The results of the study were compared with the linear regression model, showing that the artificial neural network is well optimized, allowing to predict the shallow foundation load more closely with the experimental results. The results of the study are a premise for the application of artificial neural networks in solving other problems in the field of construction.

Keywords: shallow foundation bearing capacity; genetic algorithm; artificial neural network.