针对矿井提升系统事故频次数据少的缺点,采用灰色理论进行预测。在原有的GM(1,1)模型基础上,笔者提出了自适应性GM(1,1)模型。在GM(1,1)的基础上简述了自适应GM(1,1)模型的原理、建模基本步骤和精度检验方法以及残差修正模型。通过实例分析了该方法的有效性和适用性,从而为矿井提升系统超前采取防范措施,提供了依据,将事故损失减少到最低,做到防患于未然。 Aiming at the shortcoming of few frequency data of mine hoisting system accidents, the gray theory is used to predict. Based on the original GM (1,1) model, the author proposes an adaptive GM (1,1) model. On the basis of GM (1,1), the principle of adaptive GM (1,1) model, the basic steps of modeling and the method of precision test and the residual error correction model are briefly described. The effectiveness and applicability of this method are analyzed by examples. In this way, advanced precautionary measures can be taken for the mine hoisting system to provide the basis for minimizing the accident loss so as to take precautionary measures.