April 29, 2024
Amin Keshavarz

Amin Keshavarz

Academic Rank: Associate professor
Address: Faculty of Engineering, Persian Gulf University, Bushehr, Iran
Degree: Ph.D in Civil Engineering
Phone: +98-7731222158
Faculty: Faculty of Engineering

Research

Title New Gene Expression Programming models for normalized shear modulus and damping ratio of sands
Type Article
Keywords
Normalized shear modulus, Damping ratio, Gene Expression Programming, Sands
Journal ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
DOI 10.1016/j.engappai.2015.07.022
Researchers Amin Keshavarz (First researcher) , Mohammad Mehramiri (Second researcher)

Abstract

As the most important dynamic properties of soils, shear modulus and damping ratio are two parameters employed to solve problems including seismic site response evaluation, dynamic analyses and equivalent-linear models. The work presented in this paper proposes two models for evaluation of the normalized shear modulus and two additional models for evaluation of the damping ratio of sands through Gene Expression Programming (GEP). The data used in the modeling entails the valid experimental results obtained from previous researchers. As compared to the secondary models, the first two models are more accurate with larger equation length. The parameters taken into account as model inputs consisted of shear strain, mean effective confining pressure, and void ratio. In order to evaluate the performance and accuracy, the proposed models were processed through several statistical measures such as Mean Square Error (MSE), Root Mean Square Error (RMSE) and coefficient of determination (R2). Furthermore, the relative difference between predicted and measured values was calculated, which suggested that the models were desirably accurate. Finally, the model outputs were compared against other studies, the results of which demonstrated that the proposed models are capable of estimating the dynamic parameters of sands more accurately.