| 改进的灰色GM-AR组合模型在基坑监测数据处理中的应用 |
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| 引用本文： | 徐秀杰,黄张裕,刘国超,冯建桥.改进的灰色GM-AR组合模型在基坑监测数据处理中的应用[J].测绘与空间地理信息,2015(1):200-203. |
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| 作者姓名： | 徐秀杰 黄张裕 刘国超 冯建桥 |
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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： | 灰色预测模型在变形监测领域已得到广泛的应用和发展,灰色模型在理论上可以进行中长期预测,但实际应用中随着时间的推移预测精度也随之下降,为了解决这一问题,本文对GM(1,1)模型进行了改进并将改进后的GM(1,1)模型与时间序列模型组合,利用GM-AR模型进行预测可提高模型的预测精度,并应用实例证明了该方法的可行性。
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| 关 键 词： | 变形监测 改进灰色模型 GM-AR模型 预测 |
Improved Grey GM-AR Combination Model in Foundation Monitoring Data Processing Applications |
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| XU Xiu-jie,HUANG Zhang-yu,LIU Guo-chao,FENG Jian-qiao.Improved Grey GM-AR Combination Model in Foundation Monitoring Data Processing Applications[J].Geomatics & Spatial Information Technology,2015(1):200-203. |
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| Authors: | XU Xiu-jie HUANG Zhang-yu LIU Guo-chao FENG Jian-qiao |
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| Abstract: | Gray forecast model in deformation monitoring field has been widely used and developed , gray model in theory can be long-term forecasts , but the practical application prediction accuracy over time also fall , in order to solve this problem this paper , GM (1,1) model was modified and improved GM (1,1) model combined with time series models , the use of GM-AR model to predict improve the prediction accuracy and application examples demonstrate the feasibility of the method . |
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| Keywords: | deformation monitoring gray model GM-AR model forecasting |
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