This paper put forward the frame of time series feature pattern mining(TSFPM) on the basis of domestic and international research on time series and put forward the suitable mining algorithm based on characteristic of traffic flow and realized it.
本文在分析国内外对时间序列的研究的基础上,提出了时间序列特征模式挖掘的框架,同时结合交通流的特点提出有效的挖掘算法,并且进行了算法实现。
参考来源 - 时间序列数据挖掘的研究以及在交通流预测上的应用·2,447,543篇论文数据，部分数据来源于NoteExpress
Considering all fields of text features can increase the distance between text feature pattern of each other and optimize their probability distribution.
考虑不属于该领域的文本特征，可以有效地增加不同类文本特征模式之间的距离并优化其概率分布。
Pattern matching is another feature found in many, if not most, functional languages, and offers some useful power.
模式匹配是许多（但不是大多数）函数语言中可以找到的另一个特性，它提供了一些有用的功能。
This feature can be used to support a services gateway pattern.
可以使用此功能来支持服务网关模式。
应用推荐