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Grey forecasting model refining in deformation prediction based on semi-parametric regression

机译:基于半参数回归的变形预测灰色预测模型精制

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Accurately estimating the deformation of dangerous rock is an important work for surveyors. Aiming at the limitation of the traditional GM (1,1) model, we propose that the error term in GM(1,1) model have an important influence on this model's precision and adaptability. From this point of view, a novel new model termed SRGM (1,1) is proposed. In this proposed model, the work modifies the algorithm of GM (1,1) by integrate within semi-parametric regression model to eliminate the error term resulted from the traditional calculation of background value and initial value. According to the experimental results, our proposed SRGM (1,1) model obviously can improve the precision of prediction and therefore can be adopted to deformation data analysis.
机译:准确估计危险岩石的变形是测量师的重要工作。针对传统的GM(1,1)模型的限制,我们建议通用汽车(1,1)模型中的误差术语对该模型的精度和适应性具有重要影响。从这个角度来看,提出了一种新的新模型,被称为SRGM(1,1)。在该提出的模型中,该工作通过集成在半参数回归模型内进行了改变GM(1,1)的算法,以消除由传统的背景值和初始值的传统计算产生的错误项。根据实验结果,我们所提出的SRGM(1,1)模型显然可以提高预测的精度,因此可以采用变形数据分析。

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