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。
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）。
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。
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.
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。
Longitudinal data is referred to data in which individuals are measured repeatedly through time, so it combines elements of cross-sectional data and time-series data.
纵向数据是指对每个个体在不同时间进行观测而得到的由截面和时间序列融合在一起的数据。
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.
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。
This paper puts forward a genetic programming method to find scientifically the function of side-slope lateral displacement in open-pit mines based on actual time-series data.
以时间序列实测数据为基础，提出了科学发现露天边坡变形位移函数的遗传规划方法。
Conclusions Moving seasonal mean ratio method could consider secular, seasonal, cyclic and random tendencies of time-series data together and could serve as a useful tool for prediction.
结论移动平均比率法综合考虑长期、季节、周期及随机趋势，预测效果较好。
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。
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。
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。
Among these research fields, time series data mining is a rather complex branch, which is a technique that extracts the most valuable information from large amount of history time series data.
而在这其中时间序列数据挖掘是面向特殊应用数据挖掘领域中比较复杂的一个分支，主要研究从大量时间序列历史数据中挖掘有价值信息的方法和相关技术。
Incidence degree could be used to analyse time series data in health system. There is little limit about data distribution and type of variable's correlation.
关联度分析方法可用于卫生系统内部时间序列资料的分析，该方法对数据分布类型、变量之间的相关类型限制较少。
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。
Firstly, making the time series continuous through inserting data, and secondly removing the secular displacement rate from the time series data through linear fitness.
首先对时间序列中不连续的数据进行内插处理，并通过线性拟合从时间序列中去掉长期滑动速率的影响。
While applying the method to the time series data of sedimentary rock in Talimu basin, the prediction and classification of layer in petroleum well have got solution.
在塔里木盆地沉积岩时间序列化学数据的应用实例中，解决了石油井下地层预测和归类问题。
Lastly, the feasibility and validity of the model was validated with the past years surface water resource quantity time series data from Kenswat Station on Xinjiang Manas River.
最后，以玛纳斯河肯斯瓦特站历年的年径流资料验证时间序列人工神经网络预测模型的可行性与有效性。
Financial time series has high randomicity and nonlinearity. Neural network is quite suitable in the process of financial time series data for its good ability of nonlinear mapping and generalization.
金融时间序列具有很强的随机性和非线性性，而神经网络具有良好的非线性映射能力及自适应、自学习和良好的泛化能力，因此非常适合处理金融时间序列这样的数据。
Time series data is the data set that arranges every one according to the time, and it USES social, economic and technologic fields widely.
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。
However, the oil futures prices involve the typical characteristics of time series data, nonlinearity and nonstationarity, which brings insuperable difficulties in the price forecasts.
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。
In order to improve the efficiency of filtering algorithms for time series data stream, this paper proposes a new more efficient streaming time series query filtering algorithm for DTW.
目的设计基于DTW的高效过滤算法，提高时间序列数据流的过滤查询的效率。
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.
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。
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).
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。
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。
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。
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。
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。
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。
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