| 多元时间序列聚类算法分析 |
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| 引用本文： | 郭小芳,李锋.多元时间序列聚类算法分析[J].河南师范大学学报(自然科学版),2012,40(6):142-146. |
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| 作者姓名： | 郭小芳 李锋 |
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| 作者单位： | 1. 江苏科技大学计算机科学与工程学院,江苏镇江,212003
2. 江苏科技大学电子信息学院,江苏镇江,212003 |
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| 基金项目： | 江苏省高校自然科学研究项目 |
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| 摘 要： | 为解决高多元时间序列聚类算法的问题,采用了一种基于主元分析方法的多元时间序列聚类分析方法,利用MTS序列的前z个主元与每个簇的代表元素之间的Eros距离,将原有的复杂数据降维.在此基础上通过改进K-means算法对选取的多元时间序列的主元进行聚类分析,最后得到K个MTS聚类.理论分析和实验结果表明该算法能有效解决聚类问题.
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| 关 键 词： | 多元时间序列 主元分析 k均值 聚类分析 |
Analysis of Multivariate Time Series Clustering |
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| GUO Xiao-fang
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LI Feng.Analysis of Multivariate Time Series Clustering[J].Journal of Henan Normal University(Natural Science),2012,40(6):142-146. |
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| Authors: | GUO Xiao-fang LI Feng |
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| Institution: | b (a.School of Computer Science and Engineering;b.School of Electronics and Information,Jiangsu University of Science and Technology,Zhenjiang 212003,China) |
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| Abstract: | In order to solve the problem of Multivariate Time Series clustering algorithm,an efficient clustering algorithm for Multivariate Time Series-PCA-CLUSTER is proposed.Based on Eros distance between residual MTS data and cluster representing elements,the original MTS data dimension is reduced.Subsequently,K-neighbor clustering analysis was carried out on the principal component series of MTS,and finally K MTS cluster are obtained.The experimental results show that Theoretical analysis and the algorithm is effective for solving the clustering problem. |
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| Keywords: | Multivariate Time Series principal component analysis k-means clustering analysis |
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