摘要
考虑到处于不同位置的滑坡变形监测点,由于它们所处的位置不同,各种环境因素对它们的影响及影响程度也不同,因此它们的变形规律也不同.首先通过计算比较找出剩余标准差最小的变形与时间、大气降雨量、温度相关关系的单因子模型,再将这些单因子模型通过叠加,组成多因子模型,然后将变形与时间、大气降雨量、温度相关关系的多因子模型的模型参数看作含有动态噪声的状态向量,建立卡尔曼滤波模型.实例计算表明这种建模方法效果较好.
Considering landslide deformation monitoring points in different locations, because they are in different location, it is different that all environmental factors influence them and influence extent to them, so their deformation laws are different. Firstly, the single factor model that deformation is interrelated with time, rainfall, temperature whose residual standard deviation is least is found by calculation and comparison, and these single factor models are superimposed to form a multi-factor model, then parameters of the multi-factor model that deformation is interrelated with time, rainfall, temperature are looked as state vectors that contain dynamic noises to build Kalman filter model. An example of calculation shows that the modeling method is effective.
出处
《数学的实践与认识》
CSCD
北大核心
2011年第7期86-90,共5页
Mathematics in Practice and Theory
基金
精密工程与工业测量国家测绘局重点实验室开放基金(PF2009-8)
湖北省自然科学基金(2008CDB047)
国家科学技术部三峡库区滑坡监测数据资源平台建设项目(2005DKA10600)
湖北省"十五"科技攻关计划项目(2004AA306B02)
关键词
滑坡
变形
状态向量
卡尔曼滤波
模型
landslide
deformation
state vector
Kalman filter
model
