Modelling Pore Water Pressure Using Sigmoid Kernel Function

Pore-Water Pressure (PWP) is an influential parameter for monitoring slope stability responses to rainfall especially in the area that prone to experience slope failure. Monitoring PWP that is in the form of nonlinear complex data however is expensive and require quite tedious task through traditional approach for evaluation purposes. In respond to that, recently, PWP able to be modelled by soft computing techniques - Support Vector Machine (SVM). SVM will determine the optimal linear separating plane in high dimension feature space of nonlinear complex data by its numerous kernel function technique. The data on rainfall is collected at slope site of Universiti Teknologi PETRONAS, Perak.