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滑坡会对人类生命和财产造成巨大损失,预测预报是预知滑坡灾害发生并减少其影响的重要手段。GM(1,1)算法在滑坡预测中得到普遍应用,该算法具有较少数据量建模的优点。对于滑坡不需要了解各种影响因子的具体状态,但存在建模数据量选取不确定性和长时距预测精度降低的问题,以GM(1,1)模型为基础,引用数据融合技术,对滑坡变形量进行预测,并用实测数据进行验算,结果表明该方法能提高滑坡的预测精度。
Landslides can cause huge losses to human life and property. Prediction is an important means of predicting landslides and reducing their impacts. The GM (1,1) algorithm is widely used in landslide prediction. The algorithm has the advantage of less data modeling. For the landslide, it is not necessary to know the specific state of various influencing factors, but there is a problem that the uncertainty of the modeling data amount and the prediction accuracy of the long-time span decrease. Based on the GM (1,1) model, the data fusion technique The landslide deformation is predicted and verified with the measured data. The results show that this method can improve the prediction accuracy of landslides.