Prediction of Pile Bearing Capacity Using Artificial Neural Networks.

Authors

A. Elgamal, Faculty of Engineering., El-Mansoura University., Mansoura., Egypt.
A. Elnimr, Professor of Structural Engineering Department., Faculty of Engineering., El-Mansoura University., Mansoura., Egypt.
Adel Ahmed Dif, Professor of Structural Engineering Department., Faculty of Engineering., El-Mansoura University., Mansoura., Egypt.
A. Gabr, Assistant Professor of Geotechnical Structural Engineering Department., Faculty of Engineering., El-Mansoura University., Mansoura.,Egypt.

Corresponding Author

Elgamal, A.

Subject Area

Civil and Environmental Engineering

Article Type

Original Study

Abstract

It is well known that the human brain has the advantage of handling disperse and parallel distributed data efficiently. On the basis of this fact, artificial neural networks theory was developed and has been applied to various fields of science successfully. In this study, error back propagation neural networks were utilized to predict the working bearing capacity of piles. The data of performed pile load tests are used to verify the applicability of the presented neural network procedure. The results showed that the maximum error of prediction did not exceed 25%. Thus, the use of Neural Networks to predict pile capacity seems to be feasible for practical purpose.

Recommended Citation

Elgamal, A.; Elnimr, A.; Ahmed Dif, Adel; and Gabr, A. (2021) "Prediction of Pile Bearing Capacity Using Artificial Neural Networks.," Mansoura Engineering Journal: Vol. 37 : Iss. 3 , Article 4.
Available at: https://doi.org/10.21608/bfemu.2021.156943