problem data

Again, analysis the status of teacher education of science and engineering, then illustrate the problem through survey data, next find out the countermeasures based on a careful analysis of data and research that causes the problem.

再次，分析高等理工科院校教师教育中的现状，在认真分析数据和原因的基础上，找出问题所在。

Resolve the target track problem of radar by the data fusion technology.

利用数据融合技术解决雷达目标跟踪方面的问题；

The choice of the transferring media of telemetry data is an important problem.

遥测数据需要传递，传递介质的选择是一个重要问题。

The open-data shift poses a confusing problem for junior researchers.

开放数据的改变给初级研究者造成了一个令人困惑的问题。

Owing to the high temperature tube rupture problem in the sub-critical intermediate reheated natural circuit boiler which was mounted with 18 wall temperature measured data, the cause of the tube rupture was clear, and the treatment was suggested.

针对亚临界中间再热自然循环锅炉的高温爆管问题，在锅炉安装了18个壁温测点。通过对这些壁温实测数据的分析，搞清了高温过热器爆管的原因，提出了处理的意见。

The serious problem is radio data transmission during the radio telemetry seismic equipment works in mountainous area.

无线遥测地震仪在山区施工中遇到的最大问题是无线电信号的传输。

A great deal of information exists in Internet, from which data mining is to find hidden rules, make full use of useful data, abandon unnecessary data, and solve the problem of data application quality.

因特网上有海量的数据信息，数据挖掘是从大量的数据中发现隐含的规律性内容，充分利用有用数据，废弃无用数据，解决数据的应用质量问题。

After that we analysis the acquired datas and put the analysed datas into the performance database. We propose an aggregation method to solve the problem of mass data storage which makes the platform can not show only the real-time data but also historical data.

针对庞大的数据存储的问题，设计了数据汇聚的方式，使得平台既能显示实时数据又能对历史数据进行分析。

The key problem of EPON is at what time the ONU uploads data can make the bandwidth utilization rate more highly and the delay more shortly. This problem collectively refers to as BA problem.

EPON的核心问题就是每个ONU在何时上传数据，才能够使得带宽利用率更高，时延更短，这类问题统称为BA问题。

Data stream clustering is an important issue in data stream mining. Most of the existing algorithms adopted K medians ( means) method to solve this problem, which are not suitable to address the problem of clustering high dimensional or abnormal distributed data streams.

数据流聚类是数据流挖掘研究的一个重要内容，已有的数据流聚类算法大多采用k中心点（均值）方法对数据进行聚类，不能对数据分布不规则以及高维空间数据流进行有效聚类。