【摘要】：針對(duì)斜坡單元大小直接影響地震滑坡敏感性區(qū)劃結(jié)果,論文利用河網(wǎng)密度優(yōu)選出集水面積閾值,在此基礎(chǔ)上生成最優(yōu)斜坡單元。構(gòu)建了基于遺傳算法的支持向量機(jī)敏感性分區(qū)預(yù)測(cè)模型,并實(shí)現(xiàn)了寶盛鄉(xiāng)地震滑坡敏感性分區(qū)。結(jié)果顯示,在優(yōu)選出的斜坡單元基礎(chǔ)上完成的地震滑坡敏感性分析的精度達(dá)到了98.72%。利用優(yōu)選斜坡單元結(jié)合基于遺傳算法的支持向量機(jī)構(gòu)建的地震滑坡預(yù)測(cè)模型是滑坡預(yù)測(cè)的有效工具,可為防災(zāi)減災(zāi)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(guó)地質(zhì)大學(xué)(武漢)地球物理與空間信息學(xué)院;武漢工程大學(xué)資源與土木工程學(xué)院;
【基金】：國(guó)家“863”計(jì)劃項(xiàng)目(2012AA121303)~~
【分類號(hào)】：P642.22

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本文編號(hào)：2448235