摘要
本文针对灰色理论模型在建模过程中受到随机扰动影响这一问题,提出了利用卡尔曼滤波处理建模数据的方法。经过实例检验,证明基于滤波算法的灰色理论模型在一定程度上可以提高预测值的精度,更好地反映了观测目标的变形趋势,在变形监测中具有一定的优势。
In this paper, the problem which gray model is influenced by random disturbance during the model is built, was solved by using Kalman filter to improve the quality of data. Experiment results showed that gray model based on Kalman filter could enhance the accuracy of predicted value and reflect the deformation tendency better. The method would be superior in deformation monitoring.
出处
《测绘科学》
CSCD
北大核心
2011年第4期19-21,共3页
Science of Surveying and Mapping
关键词
卡尔曼滤波
GM(1
1)模型
收敛速度
预测值
变形监测
Kalman filter
GM （ 1, 1 ） model
convergence rate
predicted value
deformation monitoring
