| 加权数据融合算法及其应用举例 |
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| 引用本文： | 刘叶玲,朱艳伟.加权数据融合算法及其应用举例[J].西安科技大学学报,2005,25(2):253-255. |
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| 作者姓名： | 刘叶玲 朱艳伟 |
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| 作者单位： | 西安科技大学,基础课部,陕西,西安,710054 |
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| 摘 要： | 建立了一种基于格罗贝斯(Grubbs)准则和聚类分析的加权数据融合算法，即先用格罗贝斯准则剔除所测数据中的疏失误差数据，再用聚类分析的方法对剔除疏失误差数据后的测量数据进行聚类，并由此确定各类别的权数(加权因子)，最后利用所得权数进行加权融合得出被测对象的融合估计值。实验证明，该算法简单有效，且适合计算机编程。
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| 关 键 词： | 数据融合算法 应用 聚类分析 疏失误差 计算机编程 测量数据 加权因子 加权融合 实验证明 估计值 权数 对象 |
| 文章编号： | 1672-9315(2005)02-0253-03 |
| 修稿时间： | 2004年4月23日 |
A weighted data fusion algorithm and its application |
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| LIU Ye-ling,ZHU Yan-wei.A weighted data fusion algorithm and its application[J].JOurnal of XI’an University of Science and Technology,2005,25(2):253-255. |
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| Authors: | LIU Ye-ling ZHU Yan-wei |
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| Abstract: | A weighted data fusion algorithm based on Grubbs's criterion and cluster analysis has been presented. Outlying observation data are eliminated by Grubbs's criterion. After the outlying observation data were eliminated, the cluster analysis method is used to cluster the testing data and decide the weights of each class. Then the estimate of the actual value is obtained by fusing the weights and the testing data. It has been proved that this algorithm is not only simple and efficient, but also convenient for programming by computer. |
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| Keywords: | Grubbs's criterion cluster analysis weight data fusion |
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