Slope stability prediction of road embankment on soft ground treated with prefabricated vertical drains using artificial neural network

Rufaizal Che Mamat (Universiti Kebangsaan Malaysia)
Abd Manan Samad (Universiti Teknologi MARA)
Anuar Kasa (Universiti Kebangsaan Malaysia)
Siti Fatin Mohd Razali (Universiti Kebangsaan Malaysia)
Azuin Ramli (Politeknik Ungku Omar)
Mohd Badrul Hafiz Che Omar (Universiti Teknologi MARA)

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 9, No 2: June 2020

This paper presents the slope stability for road embankment constructed on the soft ground treated with prefabricated vertical drains (PVDs). The slope stability was evaluated based on the factor of safety (FOS) through numerical analysis and modeled with an artificial neural network (ANN). The permeability ratio of the smear effect was verified based on a comparative analysis between field data and numerical simulation to develop the datasets used in ANN model training. A total of 75 datasets generated from numerical simulations were randomly selected into three groups for training, testing, and validation. The coefficient of determination (R2) and root mean square error (RMSE) were considered to evaluate the performance ANN model. It was found that the developed ANN model showed strong potential for predicting slope stability within the accepted range.