Susceptibility assessment of rock collapse hazards in Longjuba area based on dummy variables analysis
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摘要: 选择合适的评价模型对准确评价崩塌灾害的易发性至关重要。以磨刀溪流域龙驹坝地区崩塌灾害为对象，对设置哑变量和未设置哑变量的Logistic回归模型进行比选分析，准确建立区域崩塌灾害易发性区划。分析表明：根据Cox & Snell R2和Nagelkerke R2统计量、混淆矩阵、hosmer-Lemeshow检验的结果，设置了哑变量的回归模型对样本的拟合效果较好，对灾害发生的判对率高。设置哑变量的回归模型崩塌概率归一值集中于极易崩区和易崩区，比重和为93%；未设置哑变量的模型仅为65%，前者的区划效果更佳。
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关键词:
- Logistic回归模型 /
- 易发性评价 /
- 崩塌 /
- 哑变量
Abstract: Selecting the appropriate assessment model is crucial to the susceptibility assessment of rock collapse hazards. Taking the collapse hazards in the Longjuba area of the Modaoxi basin as an example, this article establishes a logistic regression model considering dummy variables and a logistic regression model not considering dummy variables, and the models are compared to accurately establish the susceptibility zoning. The analysis results show that according to the Cox & Snell R2 statistical results, the Nagelkerke R2 statistical results, the confusion matrix results, and the hosmer-Lemeshow results, the regression model considering dummy variables provides a better fit to the samples and a higher right percentage of classification whether collapse has occurred. In the regression model considering dummy variables, the normalized probability values of the high easy-happening area and the easy-happening area are 93%. Comparing to only 65% in the model not considering dummy variables, the former has a better zoning effect.-
Key words:
- Logistic regression model /
- susceptibility assessment /
- rock collapse /
- dummy variables
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