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。
You can use the unique function to evaluate all the unique members found in a series data object.
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。
Combining grey system theory with the feature of series data, a grey interpolation approach based on forward and back grey prediction model is proposed.
测序技术的进展为大规模序列数据的高通量分析提出了挑战。
Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data.
本文给出了四种由观测序列数据估计威布尔分布参数的方法。
Four methods are adopted to estimate Weibull distribution parameters based on observation sequence.
根据序列数据制备的多核苷酸可用作检测和鉴定相关序列的试剂。
Polynucleotides prepared according to the sequence data can be used as reagents to detect and characterize related sequences.
如果消息的次序对于您的应用程序很重要，就需要在每个消息中添加序列数据。
If the ordering of messages is important to your application, you need to add sequencing data to each message.
随着越来越多的植物基因组序列数据可用，比较注释的价值将会增加。
With the increasing availability of plant genome sequence data, the value of comparative annotation will increase.
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.
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.
一个解析引擎消耗xml序列数据，并在发现进来的XML数据的结构时回调应用程序。
A parsing engine consumes XML sequential data and makes callbacks into the application as it discovers the structure of the incoming XML data.
综上，我们认为仅仅由有限的分子序列数据获得的系统发育关系是不可靠的。
In sum, we don't believe phylogenetic relationship acquired by limited molecular sequences data is credible.
再利用平均CSR匹配置信度和一个规则匹配算法构建有效的序列数据分类器。
Then an effective sequential data classifier is constructed using average CSR matching confidence and a rule-matching algorithm.
越来越多的微生物基因组序列数据为系统地研究基因的调节和功能创造了有利条件。
The rapidly accumulating data of sequenced microbial genomes allows to conduct systematic studies on microbial gene regulation as well as function.
来源于序列数据的信息是固有地静态的，并大部分相互作用数据集也以一种静态的方式来测量。
Information derived from sequence data is inherently static, and most interaction data sets are measured in a static way as well.
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.
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.
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.
本章总结了核酸序列数据库资源，提供了如何提交序列到数据库的信息，并解释了如何访问这些序列数据。
This chapter summarizes the nucleotide sequence database resources, provides information on how to submit sequences to the databases, and explains how to access the sequence data.
本文主要对适用于生物序列数据上的后缀树索引技术和生物信息学中的多序列比对算法进行了分析和研究。
This thesis mainly focuses on the study of suffix tree index technical dealing with bio-sequences and multiple sequences alignment problem in bioinformatics.
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.
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.
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