长江科学院院报 ›› 2010, Vol. 27 ›› Issue (7): 17-21.

• 工程安全与灾害防治 • 上一篇    下一篇

典型滑坡危险度预测的距离判别分析模型

周 健1 ,史秀志1 ,郑 纬2 ,杜 坤1 ,王怀勇3   

  1. 1. 中南大学 资源与安全工程学院 , 长沙 410083 ; 2. 中南大学 地学与环境工程学院,长沙 410083 ; 3. 中国恩菲工程技术有限公司,北京 100013
  • 出版日期:2010-07-01 发布日期:2010-07-01

Distance Discriminant Analysis Model for Prediction of Hazard Degree of Typical Landslide

ZHOU Jian1, SHI Xiu-zhi1, ZHENG Wei2, DU Kun1, WANG Huai-yong3   

  1. 1. School of Resources and Safety Engineering, Central South University, Changsha 410083, China ; 2. School of Geoscience and Environmental Engineering, Central South University, Changsha 410083, China  3. China Enfi Engineering Corporation , Beijing 100038, China
  • Published:2010-07-01 Online:2010-07-01

摘要: 应用统计学理论并结合工程实际,从典型滑坡的强度指标和发生可能性指标这2个方面出发,选取滑坡规模、坡度、高差、坡体结构、地层关系、坡型、块石含量、地层和岩性9个影响因素作为判别因子,建立典型岩质滑坡危险度评价的距离判别分析模型(DDA) 。利用奉节县18个典型岩质滑坡工程实例作为学习的样本进行训练和检验 , 回判估计的误判率为0 ;利用该模型对另外6组现场数据作为预测样本进行测试,预测结果与实际情况吻合较好。研究结果表明:距离判别分析模型预测精度较高,回代估计的误判率低,是典型岩质滑坡危险度评价的一种有效新方法。

关键词: 典型滑坡, 危险度评价, 距离判别分析, 预测

Abstract:  On the basis of the Mahalanobis distance discriminant theory and in combination with the project practice, a distance discriminant analysis model of hazard degree assessment of a typical landslide was established according to the typical landslide strength indexes and the possibility indexes of the landslide, in which nine parameters were selected as the discrimination factor. The parameters are: landslide size, gradient, difference of height, slope structure, stratigraphic relations, slope shape, rubble content, stratum and lithology. Eighteen typical landslide examples in Fengjie County were used for training and verification. The back substitution method was introduced to verify the stability of the distance discriminant analysis model and the ratio of mistake-discrimination was equal to zero after the distance discriminant analysis model was trained. By means of the model, other 6 groups of measured data were tested as forecast samples, and the predicted results are consistent with the measured data. The study result shows that the distance discriminant analysis model has a higher accuracy and a low mis-discrimination ratio. It is a new approach to predict the hazard degree of a typical landslide, which can be used in practical engineering.

Key words: typical landslide , hazard degree assessment,  , distance discriminant analysis, prediction

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