为研究GM(1,1)模型初始条件对变形预测的影响,首先,讨论了不同视角下GM(1,1)初始条件选取的特点;其次,融合新陈代谢和新信息优先建模思想,提出基于初始条件滚动的RnGM模型;最后,通过实例将RnGM模型与已有的初始条件优化的GM(1,1)模型的预测结果进行比较。结果表明,RnGM具有较好的预测精度,更适合变形预测。
characteristics Reestablishment of the initial condition for GM ( 1,1 ) mode was introduced in the paper. Firstly, of different initial condition for GM ( 1,1 ) modeling has been discussed, then, a rolling initial condi- tion for GM ( 1,1 ) was established based on the fusion metabolic GM ( 1,1 ) and the principle of new information as first priority. Finally, RnGM was used to analyze and predict the deformation of surrounding rock in tunnels and subsidence of high-rise building. Comparison of the model with other models shows that RnGM model is able to improve the precision of prediction and therefore can be applied to deformation data analysis.