计算机科学 ›› 2016, Vol. 43 ›› Issue (5): 234-237.doi: 10.11896/j.issn.1002-137X.2016.05.043
陈帅飞,吕鑫,戚荣志,王龙宝,余霖
CHEN Shuai-fei, LV Xin, QI Rong-zhi, WANG Long-bao and YU Lin
摘要： 时间序列数据具有规模大、维度高等特点,直接在原始序列上进行数据挖掘,其计算复杂度高且易受噪声影响,因此对原始时间序列进行预处理是必不可少的,而常用的线性表示方法大多存在对分段点的筛选准确度不高的问题。基于时间序列的变化特征,提出了一种基于时间序列关键点的线性表示方法。该方法综合考虑了时间跨度和振幅变化,能高效提取时间序列中的关键点,并防止过度除噪,实现简单。实验表明,该方法对不同领域的数据具有良好的普适性。
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