基于斜坡单元的地震滑坡敏感性分析

发布时间：2019-03-27 13:42

【摘要】：针对斜坡单元大小直接影响地震滑坡敏感性区划结果,论文利用河网密度优选出集水面积阈值,在此基础上生成最优斜坡单元。构建了基于遗传算法的支持向量机敏感性分区预测模型,并实现了宝盛乡地震滑坡敏感性分区。结果显示,在优选出的斜坡单元基础上完成的地震滑坡敏感性分析的精度达到了98.72%。利用优选斜坡单元结合基于遗传算法的支持向量机构建的地震滑坡预测模型是滑坡预测的有效工具,可为防灾减灾提供决策支持。
[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.
【作者单位】：中国地质大学(武汉)地球物理与空间信息学院;武汉工程大学资源与土木工程学院;
【基金】：国家“863”计划项目(2012AA121303)~~
【分类号】：P642.22

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