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多维时间序列数据符号化表示方法的研究 被引量：3

Research on Data Symbolization of Multi-dimensional Time Series
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摘要 提出了一种简单高效的多维离散时间序列符号化方法,该方法用模糊自适应共振理论(Fuzzy ART)对多维时间序列数据进行聚类,实现多维时间序列数据的符号化问题。同时,通过属性相关性预处理分析,过滤掉聚类中不相关或弱相关的属性,保证了聚类算法的准确性,将提出的算法应用于多维交通流数据的符号化,效果很好。 This paper proposes an efficient method for the symbolization of multi-dimensional discrete time series, This method applies fuzzy adaptive resonance theory （ART） to select the subset of the multi-dimensional time series data, which are the clustering of the time series data and symbolizing them. At the same time, the irrelated or weakly related attributes are filtrated by the study of attributes interrelated analysis that ensures the elustering＇s veracity.
作者 王晓晔 徐晓颖 孙济洲 杜太行
机构地区 天津大学计算机科学与技术系 河北工业大学电气与自动化学院
出处 《计算机工程》 EI CAS CSCD 北大核心 2006年第12期52-54,共3页 Computer Engineering
关键词 模糊自适应共振理论 多维时间序列 符号化 聚类 Fuzzy adaptive resonance theory Multi-dimensional time series Symbolization Clustering
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献7

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二级参考文献11

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共引文献94

同被引文献23

  • 1张军,吴绍春,王炜.多变量时间序列模式挖掘的研究[J].计算机工程与设计,2006,27(18):3364-3366. 被引量：11
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引证文献3

二级引证文献5

计算机工程
2006年 第12期

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