摘要
在分析灰色单点预测模型不足的基础之上,综合考虑变形点之间的空间相关性,提出将残差修正应用于空间多点模型,引入空间多点残差修正模型。对黄河小浪底水利枢纽工程B断面沉降监测结果的分析表明,该模型整体模拟与预测相对误差绝对值之和(5个周期)为122%,优于空间多点模型的179%与GM(1,1)模型的284%。同时,短周期数据模拟(5个周期内)相对误差能够控制在20%以内,具有最好的数据拟合精度。
On the basis of the analysis of the shortage of Grey single-point prediction model, by considering the spatial correlation between the deformation observation points, the residual modification is applied in the spatial multi-point model and thus the spatial multi-point residual model is developed. By taking the subsidence monitoring data of Xiaolangdi multipurpose dam as an example, the results shows that the total absolute values of relative error （ 5 cycles） of spatial multi-point residual model is 122%, better than 179% of spatial multi-point model and 284% of GM（1,1） model. Meanwhile, this model has the best fitting accuracy with the relative error less than 20% in short-cycle fitting.
出处
《大地测量与地球动力学》
CSCD
北大核心
2010年第5期125-128,共4页
Journal of Geodesy and Geodynamics
基金
中国科学院地理科学与资源研究所前沿领域创新项目
关键词
灰色预测
变形分析
残差修正
空间多点残差修正模型
沉降监测
grey prediction
deformation analysis
residual modification
spatial multi-point residual model
subsidence monitoring
