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A New Kind of Optimized Method of Grey Prediction Model and its Applications in Deformation

机译:一种新的灰色预测模型优化方法及其在变形中的应用

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Accurately estimating the deformation of rock mass is a very important work for surveyors. Aiming at the limitation of the conventional grey GM (1,1) model, we propose that the structure methods of background value and the initial condition in grey GM(1,1) model have an important influence on this model's precision and adaptableility. From this point of view, an optimized grey model is developed. Firstly, the structure method of background value is obtained by using integrated calculating formula of background value. The new calculating formula of background value gives GM (1,1) model the ability to optimize the modeling results. Then according to the new rest first principle of the grey model, the nth component of X (1) is supposed to be the initial condition of the pessimistic differential model. By using the optimized model to analyze and predict the deformation of rock mass and comparing this optimized model with other models, we finally draw a conclusion that this optimized model is able to improve the precision of prediction and therefore can be applied to deformation data analysis.
机译:准确估计岩石质量的变形是测量师的一个非常重要的工作。针对传统灰色GM(1,1)模型的限制,我们建议将背景值和灰色GM(1,1)模型中的初始条件的结构方法对该模型的精确和适应性有着重要影响。从这个角度来看,开发了优化的灰色模型。首先,通过使用背景值的集成计算公式获得背景值的结构方法。背景值的新计算公式使GM(1,1)模型优化建模结果的能力。然后根据灰色模型的新休息第一原理,X(1)的第n个分量应该是悲观差分模型的初始条件。通过使用优化的模型来分析和预测岩体的变形并将这种优化模型与其他模型进行比较,我们最终得出结论,即该优化模型能够提高预测的精度,因此可以应用于变形数据分析。

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