Students studying for a particular degree will take a series of lecture courses which run in parallel at a fixed time in each week and may last one academic term or the whole year.
攻读特定学位的学生将在每周的固定时间同时参加一系列讲座课程，可能持续一个学期或一整年。
To escape the time period, you must complete a series of challenges posted by the elves.
为了逃离时期，你必须完成精灵们发布的一系列挑战。
Since being laid off, though, he has worked a series of part-time, low-wage, temporary positions, including selling shoes at Lord & Taylor and making sales calls for a car company.
不过，自从被解雇后，他做了一系列兼职、低薪的临时工作，包括在洛德-泰勒公司（Lord& Taylor）卖鞋，以及在一家汽车公司做销售客服。
He points out that climate data obtained from slow-growing corals around the Pacific indicate a series of unusually frequent El Ninos around the time of the Lapita expansion.
他指出，从环太平洋缓慢生长的珊瑚中获得的气候数据表明，在拉皮塔扩张时期，厄尔尼诺现象曾频繁爆发，这很不寻常。
Another speaker discussed the challenges of managing time series data, meaning that you track incoming data according to the time interval when it was recorded.
另一位演讲者探讨了管理时间系列数据的挑战，表示您依据记录所传入数据的时间间隔来跟踪该数据。
The time series of temperature are expected to be the longest possible so as to examine various modes of oscillation periods.
人们希望温度的时间系列尽可能地长，以便能研究各种波的振荡周期。
I basically know the answer: temperature is a noisy time series, so if you pick and choose your dates over a short time span you can usually make whatever case you want.
我基本上知道答案，气温是一条嘈杂的时间序列，所以如果你在一下相对较短的时间跨度里挑选数据，你可以得到任何你想要的结果。
Once you have built up a time series, you will probably want to retrieve historical data.
构建一个时间系列后，您可能想要检索历史数据。
If you create two profile items with the same data item UID, and which overlap the same time, then the AMEE API will complain as it can't form a sensible time series from the data.
如果您使用相同的数据项uid创建了两个配置项，而且时间重叠，那么AMEEAPI将会报错，因为它不能从该数据形成一个合理的时间时序。
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。
Time series estimates showed improved control of high total serum cholesterol over the past two decades in England and the United States.
时间序列估算显示过去的二十年中英格兰和美国的高血清总胆固醇控制得到改善。
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。
Examples of complicated graphs include specialized bar-and-whiskers plots, time-series with sophisticated error bars, color encodings and density plots, and many other possibilities.
复杂图形的例子包括专业化的条形图和须状图，带有完整误差的时间序列条形图，颜色编码和密度图，以及许多其他可能的图。
It is typically used for time-series-based data gathering, but is not restricted to this; static data can also be used.
它通常用于收集基于时间的数据，但是不限于此；也可以使用静态数据。
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）。
The embedded ts() function creates a time series object out of the vector glarp$livingroom.
嵌入的ts()函数通过向量glarp$livingroom创建一个时间序列对象。
So if your big data infrastructure must cope with time series, Informix is more than up to the job.
所以如果您的大数据基础架构必须处理时间序列，Informix已足够完成此工作。
In order to study further this type of time series, it is necessary to extract deterministic and stochastic components.
为了进一步研究这种类型的时间系列，有必要提取确定性和随机成分。
R provides still more tools for time series analysis. For example, we can plot the autocorrelation function for the living room temperature.
R还具有更多用于时间序列分析的工具。
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。
Experiments have shown that this method can efficiently analyze the time series of Chinese Stock Market.
试验表明，用此方法分析中国证券市场的股票时间序列非常有效。
In the final chapter, we mine stock trading data using time series method, find out the model and outliers in the data and, at last, we show the more exact forecasting model and outlier mining method.
第五章利用时间序列的方法对证券交易数据进行了挖掘，找出了数据中的模式和异常，相对传统方法而言，给出了更精确的预测模型和异常挖掘方法。
Since these variables are characterized as nonlinearities time series data, Artificial Neural networks (ANN) will be employed using back propagation algorithm as learning algorithm.
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。
Time Series: This tracks change in value of a consistent metric over time (e. g., monthly sales).
时间系列：这个跟踪随时间变化，同一度量的值变化趋势(例，月度销售)。
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。
It discusses and compares the forecasting models using neural networks and using time series.
讨论、比较了基于神经网络和基于时间序列的预测模型。
Two kinds of models are derived; load prediction model based on building model recognition and load prediction model based on time series analysis.
提出了两种类型负荷预报模型，基于建筑模型辩识的负荷预报法和基于时间序列的负荷预报法。
Two kinds of models are derived; load prediction model based on building model recognition and load prediction model based on time series analysis.
提出了两种类型负荷预报模型，基于建筑模型辩识的负荷预报法和基于时间序列的负荷预报法。
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