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？
You can use the unique function to evaluate all the unique members found in a series data object.
可以使用UNIQUE函数处理在序列数据对象中找到的所有独特成员。
RRDtool is an open source, high performance data logging and graphing system for time series data.
RRDtool是一个开放源码的高性能数据日志记录和绘图系统，用于处理时间系列数据。
Graphite is a Python web application that has been developed to provide scalable storage and visualization for numeric time-series data.
Graphite是一个PythonWeb应用，用来为数字时序数据提供可伸缩的存储和可视化显示。
You don't even have to produce an analysis on time-series data, as the tool lets you do a scatter plot to compare search trends between different data.
你甚至不必对这些时间序列数据进行分析，因为这个工具允许你做一个散点图来比较不同数据里的搜索趋势。
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。
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。
Mining time series data with association rules is a new field.
采用关联规则挖掘时序数据是较新的研究领域。
Returns predicted future or historical values for time series data.
返回时序数据的将来或历史的预测值。
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。
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。
This is because panel data consist of times series data and cross sectional data.
这是因为面板数据包括时间序列数据和横截面数据。
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。
Time series data is continuous and can be stored in a nested table or in a case table.
时序数据是连续的，可以存储在嵌套表或事例表中。
In the last, we give an example of dynamical Bayesian networks for time series data analysis.
最后给出了用于时间序列分析的动态贝叶斯网络的实例。
Times series data is one of common data types and also the important research subject of data mining.
时序数据是一种常见的数据类型，也是数据挖掘的重要研究内容。
As a result, the organization may be forced to conduct its evaluation at the corporate level using time series data.
因此，企业可能会被迫在公司层面上使用时间序列数据。
Mapping the raw time series data to a modality space effectively is a critical problem in time series similarity search.
将时序数据有效地映射到特征空间是时间序列相似性搜索的一个关键问题。
In this paper, the method TSD-PVAP, which is the pixel-oriented visualization analysis of time series data is introduced.
提出了一种基于像素的时序数据可视化分析方法TSD -PVAP。
Rough set theory, as an effective tool to deal with vagueness and uncertainty, is effective to the time series data mining.
粗糙集理论作为一种处理模糊和不确定性问题的有效工具，对时间序列的数据挖掘是有效的。
At the same time, however, the nonlinear and chaotic characteristic of time-series data makes the mining be a difficult issue.
然而，时间序列数据的非线性混沌特点，使得对它的挖掘成为难题。
The hydrological method is using the hydrological series data to establish the autoregressive and multivariate recurrence models.
水文方法是利用水文序列资料建立自回归模型和多元递推模型。
The process of knowledge discovery in time series includes preprocessing of time series data, attributes reduction and rules extraction.
知识发现的过程包括时间序列数据预处理、属性约简和规则抽取三部分。
In this paper, we extract rules of the decision table by an incremental algorithm for the dynamic decision table of the time series data.
本文对数据成时间序列的动态决策表，用增量式算法提取决策表的规则模型。
The outer frequency spectra of wind waves are estimated with the time series data of wave elevation measured in the laboratory wind wave flume.
利用实验室风浪槽内测得的波面序列资料估计风浪外频谱。
The results show that the proposed ODP is an effective and feasible technique to extract the features from the hyperdimensional time series data.
同时，以心电信号为例对ODP方法进行测试，结果表明，该方法应用于超高维数据的特征提取是行之有效的。
This hybrid model synthesizes the merits of multiple intelligent computation methods and offers a new effective solution of time series data mining.
该混合模型融合多种智能计算方法优点于一体，为时序数据挖掘提供了一种新的实用方法。
Combining grey system theory with the feature of series data, a grey interpolation approach based on forward and back grey prediction model is proposed.
根据灰色系统理论和序列数据的特性，提出一种灰插值方法。
Then we use the 1990-2008 time series data of the national and Jiangsu Province to assess the impacts of the relative price of energy to energy intensity.
并分别使用了全国和江苏省1990—2008年时间序列数据，计量分析研究了能源相对价格对于能源强度的影响作用。
Then we use the 1990-2008 time series data of the national and Jiangsu Province to assess the impacts of the relative price of energy to energy intensity.
并分别使用了全国和江苏省1990—2008年时间序列数据，计量分析研究了能源相对价格对于能源强度的影响作用。
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