Application of AHP-GWO-SVM coupling model in landslide warning. (November 2020)

• Record Type: Journal Article
• Authors: Tian, Wencai; Li, Qing; Li, Fenglin
• Is Part Of: Journal of physics. Volume 1651(2020)
• Publication Date: 2020-11
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1651/1/012008
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In recent years, landslides have become more frequent under the influence of human damage. In order to reduce the loss, improve the accuracy of landslide prediction, we can analyze the data through Analytic Hierarchy Process (AHP) algorithm, then build a Support Vector Machine (SVM) model and optimize the SVM model by Gray Wolf Optimizer (GWO) algorithm. The experimental results show that the model established by GWO and SVM after the AHP method is accurate, and the predicted results are in good agreement with the actual results. Compared with single SVM, it has higher accuracy and better results, and is more suitable for multivariable complex nonlinear landslide warning.