基于最优加权组合模型及高斯－牛顿法的滑坡变形预测研究

在对最优加权组合理论和高斯－牛顿法优化非线性模型参数的方法研究的基础上，依托于洒勒山滑坡的实际变形监测资料，建立了该滑坡变形预测的3个非线性预测模型:指数模型、Verhulst模型和灰色GM（1，1）模型；利用最优加权组合理论建立了洒勒山滑坡的最优加权组合预测模型，并运用高斯－牛顿法对各单一模型和组合模型的参数进行了优化。通过对比分析得出:组合模型的预测精度高于任何单一模型的预测精度；参数优化后各单一模型的预测精度都有不同程度的提高；参数优化后的组合模型预测精度是最高的。因此，综合运用最优组合理论和高斯－牛顿法处理滑坡预测预报模型，是提高滑坡预测预报精度的行之有效的方法。

ACTUAL CASE BASED PREDICTION MODELS FOR LANDSLIDE DEFORMATION

According to the monitored data of Saleshan landslide, three nonlinear prediction models (i.e., exponential model, Verhulst model and grey GM(1,1) model) for the landslide deformation is developed in this paper. The models are based on the studying of combined model with optimum weight and Gauss-Newton method. Then the combined model with optimum weight of the landslide is built. The parameters in each individual model and the combined model are optimized using Gauss-Newton method. By analyzing and comparing, the paper can conclude that the prediction accuracy of the combined model are higher than that of an individual model. The precision for each model after optimizing parameters using Gauss-Newton method is obviously higher than that of the models before using the optimizing parameters. The combined model with the optimizing parameters in all models has the highest precision. So, it is an effective and feasible method for improving landslide prediction to use the combined model with optimum weight and Gauss-Newton method.