| 预报模型在GPS测沉降中的应用 |
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| 引用本文： | 陈威,王解先.预报模型在GPS测沉降中的应用[J].工程勘察,2012(2):84-87. |
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| 作者姓名： | 陈威 王解先 |
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| 作者单位： | [1]同济大学测量与国土信息工程系,上海200092 [2]现代工程测量国家测绘局重点实验室,上海200092 |
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| 摘 要： | 变形监测一定程度上可以预测沉降发展趋势,本文采用灰色模型和神经网络的建模理论,介绍了GPS测沉降数据的预报处理流程,并利用上海市CORS网的数据分析GPS沉降预报,运用模型对GPS测沉降数据进行预测,最后利用中误差理论对精度进行评定,得出了灰色模型和神经网络模型在GPS沉降数据预报方面精度是可靠、精确的结论,从本文数据看神经网络预测的精度比灰色模型预测精度更符合实际。
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| 关 键 词： | GPS 沉降监测 灰色模型 BP神经网络 预报 |
The application of forecasting model in subsidence monitoring by GPS |
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| Chen Wei,Wang Jiexian.The application of forecasting model in subsidence monitoring by GPS[J].Geotechnical Investigation & Surveying,2012(2):84-87. |
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| Authors: | Chen Wei Wang Jiexian |
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| Affiliation: | 1,2 , Jlexlan 2 Department of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China; 2. Key Laboratory of Modern Engineering Surveying, SBSM, Shanghai 200092, China) |
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| Abstract: | Deformation monitoring can predict the trend of subsidence to some extent. In this paper, grey and neural network theory is used to build the model, and the forecasting process of data monitored by GPS is introduced. In addition, the data of Shanghai CORS Network is used to analyze forecasting of subsidence and the model is applied to predict the monitoring data. Finally, the precision is evaluated with the theory of Mean Square Error. With several examples, we conclude that the gray model and BP neural network forecast is reliable and accurate for GPS monitoring data. The BP neural network model is more realistic than the gray model according to the data provided by this paper. |
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| Keywords: | GPS subsidence monitoring gray model BP neural network forecasting |
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