| 形变监测数据组合预测 |
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| 引用本文： | 潘国荣,谷川.形变监测数据组合预测[J].大地测量与地球动力学,2006,26(4):27-29. |
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| 作者姓名： | 潘国荣 谷川 |
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| 作者单位： | 同济大学测量与国土信息工程系,上海,200092;国家测绘局现代工程测量重点实验室,上海,200092;同济大学测量与国土信息工程系,上海,200092;国家测绘局现代工程测量重点实验室,上海,200092 |
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| 摘 要： | 灰色模型、时间序列模型以及人工神经网络是目前应用广泛、实用效果评价较好的3种形变预测方法。提出了最优加权组合预测方法,其精度更高,更适用于对形变监测数据要求高的场合。
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| 关 键 词： | 组合预测 最优加权 灰色模型 时间序列 人工神经网络 |
| 文章编号： | 1671-5942(2006)04-0027-03 |
| 修稿时间： | 2006年5月6日 |
COMBINATION PREDICTION OF DEFORMATION MONITORING DATA |
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| Pan Guorong,Gu Chuan.COMBINATION PREDICTION OF DEFORMATION MONITORING DATA[J].Journal of Geodesy and Geodynamics,2006,26(4):27-29. |
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| Authors: | Pan Guorong Gu Chuan |
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| Abstract: | At present,Grey Model,Time Series Model and Artificial Neural Network are the three prediction methods used widely in application.This paper brings forward combining these 3 prediction methods after best weighting method,forming a combination prediction method which has the respective advantage of the 3 methods.The accuracy of combination prediction method is higher than those of above 3 methods so it is more suitable for those occasions where the deformation monitoring data should meet the high demand. |
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| Keywords: | combination prediction best weighting grey model time series artificial neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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