基于参数重要度的多元时间序列相似性查询
기우삼수중요도적다원시간서렬상사성사순
Similarity Query in Multivariate Time Series Based on Parameter Importance Degree
  • 万方数据
    计算机工程 계산궤공정
    COMPUTER ENGINEERING
    2009年 24期 54-56 ,共3页

    毛红保%张凤鸣%冯卉%吕慧刚

    모홍보%장봉명%풍훼%려혜강

    多元时间序列%相似性查询%参数重要度%特征提取%相似性度量 多元時間序列%相似性查詢%參數重要度%特徵提取%相似性度量
    다원시간서렬%상사성사순%삼수중요도%특정제취%상사성도량
    multivariate time series%similarity query%parameter importance degree%feature extraction%similarity measure
    针对多元时间序列的相似性查询问题,给出参数重要度的定义,提出一种基于参数重要度的候选集查询方法.通过对多元时间序列的SVD分解,将奇异值向量和特征矩阵作为多元序列的特征,基于线性空间中的坐标变换原理构造2个多元时间序列的相似性度量模型,实现在候选集上的精确匹配并获得最终的结果集.对飞行数据的相似性查询实验验证了该方法的有效性.
    침대다원시간서렬적상사성사순문제,급출삼수중요도적정의,제출일충기우삼수중요도적후선집사순방법.통과대다원시간서렬적SVD분해,장기이치향량화특정구진작위다원서렬적특정,기우선성공간중적좌표변환원리구조2개다원시간서렬적상사성도량모형,실현재후선집상적정학필배병획득최종적결과집.대비행수거적상사성사순실험험증료해방법적유효성.
    Aiming at the problem of multivariate time series similarity search, this paper presents the definition of parameter importance degree and puts forward a candidate sets obtaining method based on it. It extracts singular vector and eigenvector matrix as the features of multivariate time series by SVD, constructs similarity measure modal via coordinate transformation theory in linear space, realizes precise matching on candidate sets and gets ultimate results. Experiments on flight data similarity query show the validity of the method.
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