The paper presents two algorithms for efficient mining of partial periodic pattern with multiple time granularity.
提出了两种在多粒度时间下的部分周期挖掘算法。
Experimectocl results show the proposed algorithms are efficient in mining partial periodic with multiple time granularity when input is large.
实验表明了提出的算法在多粒度时间下挖掘部分周期是有效的。
After the mathematical model of multiple granularity time series is established, some notations related to the rule discovering are defined.
建立多粒度时间序列的数学模型，并对提取模糊规则中所涉及的一些基本概念作出定义。
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