边坡稳定性预测的粗糙集-距离判别模型及其应用

为克服马氏距离判别模型无法考虑指标权重的不足,引入粗糙集理论,通过分析评判方法对评价对象的支持度和重要性计算得到权重系数。将权重系数嵌入距离判别模型,构建了边坡稳定性预测的加权距离判别模型。根据边坡失稳破坏特点,选取合理的判别因子,以大量工程实例样本作为原始数据和训练样本,建立了边坡稳定性评价预测的粗糙集-距离判别模型。将边坡稳定性评价预测的粗糙集-距离判别模型评价预测结果与马氏距离判别法、支持向量机理论、Bayes判别分析等方法得到的预测结果进行了对比分析,验证了粗糙集-距离判别模型的有效性。将建立的粗糙集-距离判别模型应用于黄河中游地区某大型水利枢纽库区边坡工程,预测结果与实际情况吻合。研究结果表明,粗糙集-距离判别模型具有权重分析合理、预测准确性高等优点,是进行边坡稳定性分析预测的一种新的有效途径。

ROUGH SET-DISTANCE DISCRIMINANT ANALYSIS MODEL OF SLOPE STABILITY PREDICTION AND ITS APPLICATION

The Mahalanobis distance discriminant method has a shortage that the weight factors can't be considered. To overcome this shortage, the rough sets theory is used to analyze and obtain weight factors. The weight coefficients are computed by analyzing the support and significance of forecasting method for the predicted object. The weighted distance discriminant models of slope stability evaluation and prediction are established by introducing weight coefficients. According to the characters of slope instability and failure, the rough set and distance discriminant models of slope stability evaluation and prediction are founded, where reasonable indexes are considered and a large set of case engineering samples are taken as raw data and training samples. The validity of rough set and distance discriminant models of slope stability evaluation and prediction have been verified through contrasting with Mahalanobis distance discriminant method, support vector machine and Bayes discriminant analysis. The rough set and distance discriminant models are applied to the slope engineering at some large water control project reservoir area in the middle reaches of Yellow River. The predicting results are according with real situation. The research results show that the rough set and distance discriminant models are reasonable for weight analysis with high prediction accuracy, which is a new and effective method for slope stability analysis and prediction.