Periodicity mining is the mining of periodic patterns, that is, the search for recurring patterns in time-series database.
周期模式主要是研究时序数据库中的循环特性，是时态数据挖掘的一个重要的研究方向。
They are the foundation of research on Algorithm of Mining Partial Periodic Patterns and they can be used in the whole paper.
这作为全文研究的基础，贯穿于时间序列部分周期模式挖掘和增量挖掘分析的全过程。
Setting this value closer to 1 favors the discovery of many near-periodic patterns and the automatic generation of periodicity hints.
如果将此值设置为更接近于1的数，则允许查找许多接近周期的模式并允许自动生成周期提示。
An algorithm for efficient mining of asynchronous periodic patterns with multiple granularities by exploring some interesting properties related to asynchronous periodicity was proposed.
把异步周期和多时间粒度下的时态模型结合起来研究，并利用异步周期的特点提出了一种有效的挖掘算法。
The results indicate that periodic change of Be'nard patterns after certain time will stop automatically during pregnant period of strong earthquake.
计算结果表明，在强地震的孕育期，贝纳德花样的周期变化在一定时间后将自动停止。
Thereby, periodic images, especially image data in which background patterns such as wallpaper are arranged, can be compressed and decoded at higher speed and higher compressibility.
能够在对具有周期性的图像、特别是墙纸等排列有背景图案的图像数据进行编码时，就能够更高速地，且以更高压缩率来压缩整个图像。
Thereby, periodic images, especially image data in which background patterns such as wallpaper are arranged, can be compressed and decoded at higher speed and higher compressibility.
能够在对具有周期性的图像、特别是墙纸等排列有背景图案的图像数据进行编码时，就能够更高速地，且以更高压缩率来压缩整个图像。
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