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传统GM(1,1)模型用于预测时,该模型在初始的少量数据中,才能充分利用有限的数据反映系统的发展变化,越往后监测,该模型的预测精度就越弱。而在实际应用中,必须不断考虑那些随时间相继进入系统的扰动或驱动因素,随时将每一个新得到的数据置入系统中,建立新信息GM(1,1)模型进行动态预测。因此,针对传统GM(1,1)模型存在的不足,文章建立了灰色新陈代谢GM(1,1)滑坡预测模型,并利用该模型对巴达高速公路滑坡位移变形进行了预测。结果表明,灰色新陈代谢GM(1,1)模型精度较高,预测误差较小,有很好的工程应用价值。
When the traditional GM (1,1) model is used for forecasting, the model can make full use of limited data to reflect the development of the system in the initial small amount of data, and the more backward the model, the weaker the prediction accuracy of the model. In practical application, we must constantly consider those disturbances or drivers that enter the system one after another in time, and put each newly obtained data into the system at any time to establish a new GM (1,1) model for dynamic prediction. Therefore, in view of the shortcomings of the traditional GM (1,1) model, a prediction model of gray metabolic GM (1,1) landslide is established, and the landslide displacement deformation of Badami Expressway is predicted by the model. The results showed that the GM (1,1) model of gray metabolism has high precision and small prediction error, which has a good engineering application value.