返回时序数据的将来或历史的预测值。
Returns predicted future or historical values for time series data.
研究时序数据预报和提高预报精度的方法。
The method of predicting time series and the method of improving the accuracy of prediction were studied.
本文算法对于时序数据的聚类具有较强的鲁棒性。
Proposed dynamic clustering algorithm has strong robustness in clustering of time series multi-dimensional data.
时序数据是连续的，可以存储在嵌套表或事例表中。
Time series data is continuous and can be stored in a nested table or in a case table.
趋势分析与相似搜索是时序数据挖掘的主要技术与方法。
Trend analysis and similitude search are the main techniques and methods in time serial 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。
Times series data is one of common data types and also the important research subject of data mining.
根据课题背景，给出一个针对时序数据的离群数据挖掘算法的改进算法。
Based on the project background, an improved outlier data mining algorithm for time series data is given out.
提出了一种基于像素的时序数据可视化分析方法TSD -PVAP。
In this paper, the method TSD-PVAP, which is the pixel-oriented visualization analysis of time series data is introduced.
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。
Mapping the raw time series data to a modality space effectively is a critical problem in time series similarity search.
应用复杂系统理论和方法研究了云南地区月降雨量时序数据的非线性特性。
The nonlinearity of monthly rainfall time series in Yunnan province is investigated by using the theory of complex system.
将该算法用于某钢铁企业的电力负荷时序数据，计算结果表明了算法的有效性。
The algorithm is applied for similarity mining of the time series data of the electrical loads for a steel plant. The simulation results show the effectiveness of the algorithm.
提出了基于探索性分析的时序数据挖掘方法，采用线性回归技术建立了数学模型。
A way of time series data mining was put forward based on the exploratory analysis and the mathematics module was founded by way of using linear regression technology.
本文以三峡库区常态水质参数时序数据为研究对象，进行水质参数预测建模研究。
This thesis studies on the prediction modeling method of water quality parameters based on normal time-series data in the background of the Three Gorges Reservoir.
通过使用这种方法能够对含有时序数据的信息进行充分的挖掘并发现其中的规律。
The rules of information containing the time sequences data were discovered by using this data mining model.
针对时序数据挖掘中常见数据表示算法的缺陷，提出了基于关键点的误差检验分段算法。
To overcome the defects of data representation algorithms in temporal data mining, segmentation algorithm of key-point-based error checking is proposed.
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。
Periodicity mining is the mining of periodic patterns, that is, the search for recurring patterns in time-series database.
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。
This hybrid model synthesizes the merits of multiple intelligent computation methods and offers a new effective solution of time series data mining.
对于这些大量的时序数据进行分析处理，挖掘其背后蕴涵的价值信息，具有重要的实际意义。
It has important practical significance to analyze and process with the large number of time-series data and mine with the value of the underlying implication of information.
其次，研究了常用的时序数据趋势分析模型，并对它们的推理过程和适用性进行了详细的阐述。
Secondly, time series trend analysis models in common use are introduced, whose illative process and applicability are also expatiated.
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。
Graphite is a Python web application that has been developed to provide scalable storage and visualization for numeric time-series data.
在对时序数据进行离群检测之前，一般先将原时序数据划分为若干个子序列，以便降低计算复杂度。
General approaches for outlier detection need to divide temporal data into sub-sequences so as to reduce complexity.
比较分析中国从1992-2000年投入产出表的时序数据，概括了部门间中间投入系数的变化趋势。
The general trends of the direct input coefficient change are summarized by the comparison of Chinese series input-output tables from 1992 to 2000.
序列模式挖掘作为一种时序数据分析的有效手段，能够自动从告警中提取出有助于关联分析的情景规则。
As an effective means to analyze timed data sequential pattern mining can extract episode rules from alarms, which is helpful to analyze correlation.
对时序数据建模与辨识技术进行了分析，提出了使用鲁棒LS-SVM算法建立ARMA时序预测模型。
Time series modeling and identification techniques were analyzed and the ARMA time series model based on robust LS-SVM algorithm was proposed.
在此基础上，应用时序数据分析法，对实测得到的钻孔瓦斯涌出量序列进行计算分析，发现其具有分维特征。
On the basis of the model and by applying time series analysis, it is discovered that the site measurement series of continuously dynamic gas emission possesses fractal property.
在股价时序数据不存在噪音的假设前提下，利用相空间重构技术对中国股票市场的混沌与分形特征进行实证研究。
Under the hypothesis of empty of noise, utilizing technology of phase-space reconstruction to empirically study the chaos and fractal feature of China stock market.
针对时序数据中的复杂模式问题，提出了一种时序模式算法，并描绘了算法的基本思想及给出了算法的简单伪代码。
In the paper, being directed to the complex model of time-series pattern, drawing idea and giving pseudo code of the algorithm of finding time-series patterns has been presented.
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.
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.
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