An application of SVM-based Classification in Landslide Stability

被引：10
|
作者：
Jiang, Tingyao [1 ]
Lei, Peng [1 ]
Qin, Qin [1 ]
机构：
[1] China Three Gorges Univ, Coll Comp & Informat Technol, Yichang, Hubei Province, Peoples R China
来源：
INTELLIGENT AUTOMATION AND SOFT COMPUTING | 2016年 / 22卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Landslide; Stability evaluation; SVM;
D O I：
10.1080/10798587.2015.1095480
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The calculation method of landslide stability is a critical issue in landslide research. SVM-based multi-classification algorithm, which can structure multiple binary classifiers to accomplish the multi-classification task is used for landslide stability analysis. In this paper, the slope height, slope angle, capacity, internal friction angle and cohesion are selected as impact factors affecting the stability of landslide. Loop crossover method is used to verify the accuracy of the algorithm. Compared with the Mahalanobis distance and Bayes discriminant, the proposed algorithm has a better prediction result, but it also has the largest mis-judgment loss. The accuracy of Bayes discriminant is less than the SVM, but its mis-judgment loss is minimal.
引用
收藏
页码：267 / 271
页数：5
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