| 混合模型在沉降监测中的组合预测方法 |
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| 引用本文： | 邱 伟,黄 腾,朱春宁.混合模型在沉降监测中的组合预测方法[J].测绘工程,2014(4):51-54. |
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| 作者姓名： | 邱 伟 黄 腾 朱春宁 |
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| 作者单位： | 河海大学地球科学与工程学院,江苏南京210098 |
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| 摘 要： | 对建筑物沉降数据进行建模预测,以便掌握其变形规律并预测变形趋势,保障建筑物的安全。单一预测模型有自己的适用情形,也存在各自的缺点,已经不能满足当前的精度要求。选取灰色GM(1,1)和自回归两种常用的预测模型,通过两种不同的方式进行组合预测,并结合南京市地铁一号线百家湖段沉降监测数据进行计算分析,结果表明两种组合方法与单一预测模型相比精度均有所提高。
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| 关 键 词： | 灰色GM( )模型 自回归模型 组合预测 加权平均 趋势分离 |
The combination prediction methods of mixed model used in subsidence monitoring |
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| QIU Wei,HUANG Teng,ZHU Chun-ning.The combination prediction methods of mixed model used in subsidence monitoring[J].Engineering of Surveying and Mapping,2014(4):51-54. |
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| Authors: | QIU Wei HUANG Teng ZHU Chun-ning |
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| Institution: | (College of Geoseience and Engineering, Hehai University, Nanjing 210098,China) |
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| Abstract: | In order to predominate the regular pattern, predicte the deform trend and guarantee the security of the building, it is necessary to carry on modeling forecast with the data of building settlement. Every prediction model has its own applicable situation and shortcoming which is unable to meet current accuracy requirements. Two commonly-used prediction models, gray GM （1, 1） and autoregressive model are selected in two different ways. The subway settlement monitoring data of Baijiahu station in Nanjing Metro Line one are calculated and analyzed which shows that the two combinations have an improved forecast accuracy compared with single model. |
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| Keywords: | gray GM（1 1） model autoregressive model combination prediction weighted average trendsseparation |
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