An Improved Classification Algorithm Applied on Landslide Dam Disaster Events Detection
Bai Hua1, Wang Shaoyu2
Transactions on Machine Design, Vol. 3, No. 2, 2015.
DOI: 
Link: http://www.dline.info/tmd/fulltext/v3n2/v3n2_2.pdf
Abstract:
Landslide dam is formed when a river is blocked by some kind of mass wasting such as the debris and rocks.
Landslide dams frequently fail soon and lead to upstream and downstream flooding, which could cause high casualties and
economic losses. So it is important to predict landslide dam stability for reasonable subsequent disposal. This study proposes
an improved model for landslide dam disaster events detection based on Support Vector Machine and Ridge Regression. The
improved model introduces Support Vector Machine method into traditional Ridge Regression algorithm and get an
combinational algorithm, named Combinational Ridge Regression- Support Vector Machine(CRR-SVM) algorithm. This
research chooses a record dataset about landslide damâ€™s variables to test the effectiveness and superiority of the new method;
experiment result shows that the boosting approach is more effective than previous methods.