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A novel support vector machine (SVM) model that combines kernel principal component analysis (KPCA) with particle swarm optimization (PSO) is proposed for identifying debris flow hazard degree. The proposed model consists of three stages. First, KPCA is used to extract nonlinear feature information and solve the linear correlation of input data. Second, PSO is implemented to optimize the selection...
Susceptibility is an important issue in debris flow analysis. In this paper, 26 large-scale debris flow catchments located in the Wudongde Dam site were investigated. Seven major factors, namely, loose material volume per square kilometer, loose material supply length ratio, average gradient of the main channel, average hill slope, drainage density, curvature of the main channel, and poor vegetation...
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