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An Improved Classification Algorithm Applied on Landslide Dam Disaster Events Detection
| Content Provider | Semantic Scholar |
|---|---|
| Author | Shao-Yu, Wang |
| Copyright Year | 2016 |
| 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 RegressionSupport Vector Machine(CRR-SVM) algorithm. This research chooses a record dataset about landslide dam’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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.dline.info/tmd/fulltext/v3n2/v3n2_2.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
