Abstract
This paper examines the capability of a least square support vector machine (LSSVM) model for slope stability analysis. LSSVM is firmly based on the theory of statistical learning, using regression and classification techniques. The Factor of Safety (FS) of the slope has been modelled as a regression problem, whereas the stability status (s) of the slope has been modelled as a classification problem. Input parameters of LSSSVM are: unit weight (γ), cohesion (c), angle of internal friction (ϕ), slope angle (β), height (H) and pore water pressure coefficient (ru). The developed LSSVM also gives a probabilistic output. Equations have also been developed for the slope stability analysis. A comparative study has been carried out between the developed LSSVM and an artificial neural network (ANN). This study shows that the developed LSSVM is a robust model for slope stability analysis.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.