因此，企业可能会被迫在公司层面上使用时间序列数据。
As a result, the organization may be forced to conduct its evaluation at the corporate level using time series data.
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。
At the same time, however, the nonlinear and chaotic characteristic of time-series data makes the mining be a difficult issue.
本文主要研究了时间序列数据挖掘方法中的序列模式和相似性搜索。
This paper analyses all kinds of algorithms used on sequential pattern mining and discusses traditional similarity search techniques.
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。
The process of knowledge discovery in time series includes preprocessing of time series data, attributes reduction and rules extraction.
目前对于时间序列数据挖掘的研究主要集中在相似性搜索和模式挖掘上。
Opposite to mature part of data mining (such as mining of database association rules and classify rules), mining of time series still falls into a new branch.
但是，该方法不能反映具有时间序列数据的变化特征与趋势，无法提供正确的决策支持。
But the method can't timely and accurately reflect the change characters and the trends of the time series, and can't supply the right decision-making.
时间序列数据在数据库数据中十分普遍，于是对时间序列进行数据挖掘已成为当前研究的焦点之一。
As a very common type of the data sets, time series has been one of the focuses of the current data mining research.
由于这些变量具有非线性时间序列数据，用人工神经网络(ANN)将使用反向传播算法作为学习算法。
Since these variables are characterized as nonlinearities time series data, Artificial Neural networks (ANN) will be employed using back propagation algorithm as learning algorithm.
时间序列分析所论及的就是对这种依赖性进行分析的技巧，这要求对时间序列数据建立随机动态模型。
What time series mention is the analytical technique to this kind of dependence. This requires found stochastic and dynamic models of time series.
时间序列数据就是按时间先后顺序排列各个观测记录的数据集，广泛存在于社会、经济、技术等领域中。
Time series data is the data set that arranges every one according to the time, and it USES social, economic and technologic fields widely.
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。
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.
时间序列存在于社会的各个领域，对于时间序列数据挖掘的研究目前主要集中在相似性搜索和模式挖掘上。
Recently the study on data mining of time series mainly concentrates on both the similarity search in a time series database and the pattern mining from a time series.
纵向数据的最大优点就是它将截面数据和时间序列数据结合在一起，更好地分析出个体随时间的变化趋势。
The prominent advantage of longitudinal data is that it can analyze effectively the change of individuals over time.
然而石油期货价格具有时间序列数据的典型特点，即非线性和非平稳性，这给价格的预测带来了极大的困难。
However, the oil futures prices involve the typical characteristics of time series data, nonlinearity and nonstationarity, which brings insuperable difficulties in the price forecasts.
本文利用1978 ~ 2004年的时间序列数据，运用计量方法分析我国农业贷款对农业产出增长的影响。
Basing on the time sequence data (1978-2004), this essay analyses the influence of agricultural loan on the development of agricultural economy by using metric method.
运用出口贸易增长的动因模型，选取时间序列数据，尝试对影响广东出口贸易增长的动因进行实证分析与研究。
With the factor model of export trade growth, by sampling chronical data, the paper probes into the factors promoting Guangdong export trade growth.
本课程意在达到两个目标：它提供了运算时间序列数据的工具并且对于时间序列模型的理论也会做基础的介绍。
The course intends to meet two goals. It provides tools for empirical work with time series data and is an introduction into the theoretical foundation of time series models.
赫斯特指数的计算过程需要对研究的时间序列数据进行分组，而不同的分组情况对赫斯特指数会产生不同的影响。
The calculation process of Hurst index needs to group the data of time sequence. And different grouping situations have different influences on the Hurst index.
对于一个实际的时间序列数据，我们并不知道其真正的数据生成过程，只能通过假设和基于假设的统计推断来确定。
We have to draw statistical inference by hypothesis testing, because we don't know the real data generation process of any time series.
另外，本文用模糊集理论对时间序列数据挖掘过程中的不确定性进行了处理，提出了一种模糊时序数据挖掘的框架。
Moreover, fuzzy sets theory is adopted in the dissertation to deal with the uncertainty of the mining process and a new fuzzy frame of TSDM is given then.
它是由一个简单的表达式语言驱动的，你用来检索时间序列数据，进行计算，找出复杂的问题的答案，并可视化的结果。
It's driven by a simple expression language you use to retrieve time series data, perform calculations to tease out the answers to complex questions, and visualize the results.
为刻划心脏节律存在的确定性动力学特征，运用不稳定周期轨道分析方法对健康青年人的RR间期时间序列数据进行分析。
To characterize the deterministic dynamics in heart rhythm, the unstable periodic orbit analysis were the RR interval time series of healthy young men.
对相依时间序列数据，在一定的条件下已有人证明了局部多项式加权回归系数估计服从渐近正态分布，其中核函数是有界的。
Fan J and Gijbels I gave the asymptotic normality of local polynomial regression estimation in dependent time series, where the weighted function is bounded.
时间序列数据是一种复杂的数据对象，在社会生活中的各个领域广泛存在着大量的时间序列数据有待于进一步的分析和处理。
Time series is very important and complicated data object. There are a lot of time series need to be further analyzed and processed in the all kinds of areas in society.
在日常生活中广泛存在着各种时间序列数据，发现时间序列知识、对时间序列进行预测正成为数据挖掘与知识发现的重要内容。
In our daily life, there are various kinds of time series data, and time series prediction becomes one of the important aspects of data Mining and Knowledge Discovery (DMKD).
单位根检验是计量经济学中检验时间序列数据平稳性的最重要工具，而协整检验则是用来判断非平稳变量之间是否存在长期均衡关系的常用方法。
As an important tool of testing time series stationarity, unit root test is always used, and cointegration test is also often implied for judging long equilibrium between nonstationary variables.
URI版本控制 […]是一种设计决定，用于当资源不随时间的变迁而变化时，我们为状态的改变创建新资源（类似于管理数据库中的时间序列数据）。
URI versioning […] is a design choice when resources are immutable across time and we create new resources for state changes (similar to how we manage time-series data in a database).
URI版本控制 […]是一种设计决定，用于当资源不随时间的变迁而变化时，我们为状态的改变创建新资源（类似于管理数据库中的时间序列数据）。
URI versioning […] is a design choice when resources are immutable across time and we create new resources for state changes (similar to how we manage time-series data in a database).
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