Grey Forecasting Model Refining in Deformation Prediction Based on Semi-Parametric Regression

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 204-208)
• Pages: 2731-2735
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.204-208.2731
• Online since: October 2012
• Authors: Ning Gao, Xi Min Cui
• Keywords: Deformation Prediction, Error Terms, GM(1,1) Model, Regularizing Matrix, Semi-Parametric Regression Model, Smoothing Factor

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