摘要
选择地貌特征(包括地形坡度、沟谷切割状况、洼地封闭状况、前缘临空状况)、滑面特征(包括滑面倾角、滑面形态、滑面阻抗比)、滑体结构和近期活动迹象4大类9个因子作为古(老)滑坡类潜在滑坡的判识指标,以三峡库区和岷江上游地区相同数量的典型滑坡作为学习样本,依据距离判别分析(DDA)和Fisher线性判别分析(FLDA)方法,分别建立了两个研究区潜在滑坡的DDA判识模型和FLDA判识模型。实例分析结果表明,DDA方法对两个研究区学习样本和测试样本的误判率均为0,而FLDA方法对两个研究区测试样本的误判率分别为5.56%和11.11%,对学习样本的错判率分别为11.1%和0%。因此,在三峡库区和岷江上游地区潜在滑坡的判识中,DDA法比FLDA法判识准确性更高、适用性更强。
In view of old landslides, four kinds of indices including nine secondary factors, i.e. landform characters, slip surface characters, landslide body structures and recent activities signs, were chosen as the discrimination indices for potential landslides. According to discriminant analysis theories, distance discriminant analysis（DDA） models and Fisher liner discriminant analysis（FLDA） models were respectively built for potential landslides in the Three Gorges Reservoir and the upper Minjiang River areas based on the same number of training samples. The results show the error rates of DDA method were both 0% for testing and training samples, while the error rates of FLDA method were respectively 11.1% and 0% for testing samples and 5.56% and 11.11% for training sample in the two study areas. So, DDA method has much higher prediction accuracy than that of FLDA method for discrimination of potential landslides in the two study areas.
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2011年第1期186-192,共7页
Rock and Soil Mechanics
基金
中科院知识创新工程重要方向项目(No.KZCX2-YW-Q03-5-2)
中科院山地灾害与地表过程重点实验室开放基金项目(No.110100L104)
国家科技支撑计划项目(No.2006BAC10B04)
国家自然科学基金项目(No.40802072)
关键词
距离判别分析法
Fisher判别分析法
潜在滑坡
判识指标
判识模型
distance discriminant analysis
Fisher liner discrimination method
potential landslides
discrimination index
discrimination model
