A study of slope stability prediction using least square support vector machine

• Autorzy: Samui P.
• Języki publikacji: EN

Abstrakty

EN

The determination of stability of slope is an important task in geological engineering practice. This paper proposes the use of the least square support vector machine (LSSVM) for the determination of stability of slope. The LSSVM is a statistical learning method which has a self-contained basis of statistical-learning theory and excellent learning performance. The five input variables used for the LSSVM model in this study are the unit weight (d), cohesion (c), angle of internal friction, slope angle, height (H) and pore water pressure coefficient (ru). The LSVM model also gives a probabilistic output. This study shows that the LSSVM model is a robust tool for slope stability analysis.

Słowa kluczowe

EN

slope stability; least square support vector machine; prediction; statistical learning algorithm

PL

stabilność stoku; prognozowanie

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mechanics and Engineering
• Rocznik: 2012
• Tom: Vol. 17, no. 1
• Strony: 279--287
• Opis fizyczny: Bibliogr. 24 poz., tab., rys.

Twórcy

autor

Samui P.

• Centre for Disaster Mitigation and Management VIT University Vellore-632014, INDIA,

Bibliografia

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