In this paper, we analyze given stock-time-series.
本文中，我们分析了给定的股票时间序列。
High dimensionality is the main difficulty of similarity search over time-series data.
数据的高维度是造成时序数据相似性搜索困难的主要原因。
The model is run as a time series.
模型作为时间序列运行。
How to detect if change in time series data is no longer significant?
如何检测是否在时间序列数据的变化不再明显？
Their weekly series, farfrom getting stale, has only grown more interesting over time.
他们的每周系列，一点也不会变得陈旧，而且还随时间变得越来越有趣。
Research on time series data mining is one of important hot spots of data mining.
目前时间序列的数据挖掘是数据挖掘的重要研究热点之一。
A time series data set is a sequence of random variables indexed by time.
时间序列数据是以时间为指标的一个随机变量序列。
Sell it to the museum and name it the "Frozen in Time" series.
把它卖给博物馆，命名为“冻结时间”系列。
The prediction of time series is very important in the economic and engineering fields.
时间序列的预测在经济和工程领域具有十分重要的意义。
This paper discusses the prediction of power load by time series modelling.
本文讨论如何应用时间序列建模预测电力负荷。
Fund flow is a function of time series.
资金流转是时间序列的函数。
The grey system has a high precision for the time series prediction.
灰色系统预测法对时间序列的预测有较高的精度。
Similarity Search Model of Hydrological Time Series.
水文时间序列相似性查找模型。
This paper presents a method of forecasting chaotic time series.
本文提出一种混沌时间序列预测技术。
Trend is one of the most important characters of economic time series.
趋势是经济时间序列最主要的特征之一。
Thus, testing unit root in seasonal time series is necessary.
这样对季节性时间序列进行单位根检验是很必要的。
First, the testing data must be interpolated and the basic time series must be built.
对经过预处理的测试数据进行三次样条插值，得到基本时间序列。
Research and teaching: time series econometrics and empirical finance.
主要研究和教学领域：时间序列计量经济学、实证金融。
TIS(Temporal Information System)is the formalization of time series.
时态信息系统（TIS）是时间序列的形式化表示。
The time series similarity measure and its characteristics were studied.
剖析了时间序列的相似性度量及其特点。
Time series data set comes with a temporal ordering.
时间序列数据集伴随着一个时间上的排序。
The results show that dissolved oxygen time series of river basin has chaotic property.
结果表明，河流溶解氧时间序列具有混沌特性，其外在表现为貌似随机的无规则特点；
Finally, the random error model of HRG is established by using time series analysis method.
最后，采用时间序列分析方法建立了半球谐振陀螺的随机误差模型。
First, time series models are used for prediction.
第一步使用时间序列模型进行预测研究。
Chaotic economic time series are studied by using time series analyzing methods.
利用时间序列分析方法对混沌经济时间序列进行研究。
On runoff time series forecasting, this method shows a good result, too. 3.
研究还表明，该方法在水文月径流时间序列的预测中同样有效。
Finally, we use time series method to predict the output of the next few years.
运用时间序列法对未来几年的产量进行预测。
Time series data set comes with a temporal ordering.
时间序列数据是以时间为指标的一个随机变量序列。
By clustering of traffic flow time series, the typical traffic fluctuation patterns can be found.
采用聚类分析方法对交通流时间序列进行分析可以发现典型的交通流变化模式。
By clustering of traffic flow time series, the typical traffic fluctuation patterns can be found.
采用聚类分析方法对交通流时间序列进行分析可以发现典型的交通流变化模式。
应用推荐