Prediction of Soil Pore Water Pressure Using Polynomial Kernel Support Vector Machine

Knowledge in soil pore water pressure is important in slope stability analysis. The fluctuation of soil pore water pressure is mainly affect by the rainfall intensity. The pore water pressure can cause effect on the soil strength. A few problems has been identified in obtaining the pore water pre...

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Bibliographic Details
Main Author: Muhd Hasbi, Muhamad Alif
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2017
Subjects:
Online Access:http://utpedia.utp.edu.my/23027/1/FINAL%20DISSERTATION.pdf
http://utpedia.utp.edu.my/23027/
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Summary:Knowledge in soil pore water pressure is important in slope stability analysis. The fluctuation of soil pore water pressure is mainly affect by the rainfall intensity. The pore water pressure can cause effect on the soil strength. A few problems has been identified in obtaining the pore water pressure reading which are time consuming and intensive labor work that are from field instrumentation. However, the development of soft-computing in nowadays has become focus as alternative technology to monitor the changes of pore water pressure in soil, and scope in this study is to use support vector machine. Then, a study on developing a model to predict the soil pore water using polynomial kernel support vector machine and to evaluate the model performance has been conducted. A considerable good correlation between observed and predicted pore water pressure has been found by the end of the studies with performance evaluation of R2 and RMSE of 0.93 and 0.60 respectively A slope in Universiti Teknologi PETRONAS, Perak has been chosen as study scope to predict the soil pore water pressure.