Prediction of California Bearing Ratio by Multi-Expression Programming

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Narongdej Intaratchaiyakit


California Bearing Ratio (CBR) is a crucial experiment for civil work, such as dams and pavement. CBR is always experimental in the lab, using time-consuming, expensive, and challenging processes that have an effect on how quickly building projects move forward. Hence, the model development used six multi-expression programming (MEP) models that had diverse input variables. Model I was the most proper MEP model because Model 1's coefficients of determination were relatively high in the training and testing sets. When the MEP model is compared to the multiple linear regression (MLR) and artificial neural network (ANN) models, the MEP model is found to be the most suitable model, and the MEP model can be employed because of its high level of reliability. The mathematical equation from the MEP model is applied to predict the CBR values for preliminary design in geotechnical work to reduce cost and time.


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Intaratchaiyakit, N. (2023). Prediction of California Bearing Ratio by Multi-Expression Programming. Rajamangala University of Technology Tawan-Ok Research Journal, 16(2), 1–13. Retrieved from
Research article
Author Biography

Narongdej Intaratchaiyakit, Rajamangala University of Technology Tawan-ok, Uthenthawai Campus 225 Phayathai Road Pathumwan, Bangkok 10330, Thailand

Faculty of Engineering and Architecture Department of Civil Engineering 


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