摘要
为探讨Bayes理论在区域斜坡稳定性评价中的应用,将巫山县城新址西区作为研究区,综合应用GIS技术和多元统计技术建立了区域斜坡稳定性分析的2个Logistic多元回归模型,即趋势表面模型和因子模型。趋势表面模型的自变量是位置坐标,因子模型的自变量是影响斜坡稳定的因子,包括地形坡度、高程、坡向、岩性、坡形、距有影响构造线的距离。将趋势表面模型结果作为Bayes模型中的先验信息,将因子模型结果作为Bayes模型中的样本信息,通过Bayes基本原理,得到Bayes综合模型。结果表明,在研究区内,因子模型的拟合度为80.33%,Bayes模型的拟合度为80.61%,后者得出的滑坡发生样本的判对率比前者提高了约7%,说明Bayes模型可用于区域斜坡稳定性概率评价。
In order to discuss the application of Bayesian theory in the regional slope stability evaluation, the western new urban area in Wushan County is selected as the study area. Based on GIS and multivariate statistics techniques, two Logistic multivariate regression models,trend surface model,and factor model, are applied. The independent variable of the former is location coordinates, and those of the latter are landform, physiognomy, slope, lithological character, slope shape and the distance of the influential constructive lines, etc, which may influence the slope＇s stability. The results of both models can be the prior information and sample information of Bayes model, separately. The Bayesian comprehensive model can be obtained from the Bayesian basic theory. The results from this study area show the fitness of factor model and the Bayesian model are 80.33% and 80.61%, respectively. The latter of actual landslide occurrence has increased about 7%, which can be employed in the regional slope stability probability evaluation.
出处
《地质科技情报》
CAS
CSCD
北大核心
2005年第3期85-88,共4页
Geological Science and Technology Information
基金
国家自然科学基金资助项目(40072085)
