论文部分内容阅读
滑坡的发生具有不确定性。针对目前基于位移的滑坡临滑时刻预测模型的预测结果之间存在较大的差异且难以选择出适合某种类型滑坡的最佳模型的问题,利用模糊积分具有较好处理客观证据和主观期望的优势,选择7个已知滑坡,分别用基于位移的滑坡临滑时刻预测的Verhulst、Verhulst反函数和福囿模型进行预测实验。通过计算各预测模型的隶属度获得模型的模糊密度,实现基于模糊积分融合方法的多模型综合预测。实验表明:模糊积分方法提高了已知滑坡的预测精度,使每个滑坡的预报时刻均在实际发生的前15天以内。
The occurrence of landslides is uncertain. There is a big difference between the prediction results of the current landslide prediction model based on displacement and it is difficult to select the best model suitable for a certain type of landslide. The use of fuzzy integral has the better handling objective evidence and subjective expectations In this paper, seven known landslides are selected, and the prediction experiments are carried out using the Verhulst, Verhulst inverse function and the bifold model predicted by the displacement-based landslide moment of slip. By calculating the membership degree of each prediction model, the fuzzy density of the model is obtained, and the multi-model synthesis prediction based on fuzzy integral method is realized. Experiments show that the fuzzy integral method improves the prediction accuracy of the known landslides so that the prediction time of each landslide is within the first 15 days of the actual occurrence.