吉林大学学报(地球科学版) ›› 2015, Vol. 45 ›› Issue (5): 1470-1478.doi: 10.13278/j.cnki.jjuese.201505201
邱丹丹1,2, 牛瑞卿1, 赵艳南1, 武雪玲1
Qiu Dandan1,2, Niu Ruiqing1, ZhaoYannan1, Wu Xueling1
摘要:
以地震滑坡作为研究对象,选取"4·20"芦山地震中芦山县为研究区,结合多源数据,在相关分析后选取10个评价因子,分别是地面高程、坡度、坡向、斜坡形态、地层、斜坡结构、断层平均距离、水系平均距离、植被指数和地震峰值加速度,在数字高程模型基础上采用集水区重叠法划分斜坡单元,再对各评价因子重采样,进而利用基于遗传算法的神经网络算法构建地震滑坡危险性评价模型,完成地震滑坡危险性区划。将基于斜坡单元的危险性区划结果和基于格网单元的区划结果进行比较,结果显示滑坡正确率分别为96.6%和92.6%,斜坡单元的正确率较高;同时通过多组数据的受试者工作特征曲线分析本评价模型的不确定性,每组曲线位置及曲线下面积大小相当。
中图分类号:
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