Application of Multi-Classification Support Vector Machine in the Identifying of Landslide Stability
Based on multi-classification support vector machine theory, multi-classification support vector machine model for landslides stability evaluation was built, by using 37 typical landslides in the Three Gorges reservoir areas, and was compared with distance discrimination analysis method. The results indicates that the accuracy rates of the SVM model for testing samples and training samples are up to 100%, while the accuracy rates of the distance discrimination method for testing samples and training samples are separately 80% and 77.8%.