【摘要】：針對斜坡單元大小直接影響地震滑坡敏感性區(qū)劃結果,論文利用河網(wǎng)密度優(yōu)選出集水面積閾值,在此基礎上生成最優(yōu)斜坡單元。構建了基于遺傳算法的支持向量機敏感性分區(qū)預測模型,并實現(xiàn)了寶盛鄉(xiāng)地震滑坡敏感性分區(qū)。結果顯示,在優(yōu)選出的斜坡單元基礎上完成的地震滑坡敏感性分析的精度達到了98.72%。利用優(yōu)選斜坡單元結合基于遺傳算法的支持向量機構建的地震滑坡預測模型是滑坡預測的有效工具,可為防災減災提供決策支持。
[Abstract]:In view of the slope element size directly affects the results of seismic landslide sensitivity regionalization, this paper uses river network density to optimize the threshold value of catchment area, on the basis of which, the optimal slope element can be generated. The prediction model of sensitivity of support vector machine based on genetic algorithm is constructed, and the seismic landslide sensitivity zone of Baosheng township is realized. The results show that the accuracy of seismic landslide sensitivity analysis based on the optimized slope element is 98.72%. The seismic landslide prediction model based on genetic algorithm and support vector mechanism based on genetic algorithm is an effective tool for landslide prediction. It can provide decision support for disaster prevention and mitigation.
【作者單位】： 中國地質(zhì)大學(武漢)地球物理與空間信息學院;武漢工程大學資源與土木工程學院;
【基金】：國家“863”計劃項目(2012AA121303)~~
【分類號】：P642.22

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