数据挖掘

ABSTRACT Feature analysis of financial time series has already been one of the most hotspot issues in financial field.

金融时间序列特征分析一直是金融领域中最受关注的热点问题之一，利用数据挖掘技术提取金融数据中蕴藏的有用信息，解决信息爆炸和知识获取的瓶颈问。。。

The mature arithmetic of data mining needs the high quality data to support.

成熟的数据挖掘算法需要高质量的数据来支持。

It first introduce the destination of data mining, the main techniques, system structure and running process, then describes basic theories and Apriori algorithms of association rules mining particularlly, through analysis and explanation, it refers to confidence and supportance.

它首先介绍了关联规则挖掘研究的现状以及研究的目的和意义，并给出数据挖掘的体系结构和运行过程。

Data mining for traversal patterns has been found useful in several applications. However, traditional model of traversal patterns mining only considered unweighted traversals.

遍历模式数据挖掘方法已经在多种应用中被提出，传统的遍历模式挖掘仅仅考虑了非加权遍历。

A data precessing method is provided through constructing the power transformer fault information data warehouse, based on analyzing and reorganizing the various existing data sources, the transformer failure diagnosis and early failure predication can be benefit from OLAP (On-Line Analysis Processing) and data mining technology.

为了进行变压器状态和故障自动预测，以及便于维护人员对于变压器状态进行人工预测，提出了构建电力变压器数据仓库的数据处理思想，在对有关变压器信息的多种数据源进行分析和重新组织的基础上，利用联机分析处理和数据挖掘技术，可对变压器故障诊断和早期故障预测起到积极作用。

The chief points of this paper are summered as follows: Firstly, the dynamic rule-adjusting algorithms in Snort is analyzed. Secondly, some methods to improve the algorithms are discussed and the results of experiment are obtained. Thirdly, a kind of anomaly detection models using association rule mining algorithm is put forward, and the improvements of Apriori algorithm are pointed out. Fourthly, the advantage of the new algorithm and the feasibility of this model are testified. Lastly, a framework of distributed intrusion detection system based on data mining is designed, and distributed cooperation concepts and many detecting methods are adopted in order to guarantee the accuracy and completeness of the detecting system.

论文的主要工作如下：本文分析了Snort中的动态规则调整算法，讨论了一些改进的思路，给出了实验结果；提出了一种运用关联规则挖掘算法进行异常检测的模型，根据入侵检测的实际情况对Apriori算法进行了改进，通过实验证实了改进算法的优越性和模型的可行性；设计了一种基于数据挖掘的分布式入侵检测系统框架，采用分布式协作思想，结合多种检测方法，保证了系统检测的准确性和完备性。

To find a right method for systematizing a great number of lightning data , this paper analyzes 40 893 lightning data obtained on two lines in one year.

为解决目前大量的雷电观测数据没有在防雷工作中得到很好的利用，需寻找合适方法对其进行全面整理的问题，利用已在诸多行业包括电力行业中得到应用的数据挖掘技术分析处理了某地区两条线路上一年观测所获得的40893条雷电数据。

In our work here,a model of data mining was developed,which got its foundation from Artificial Neural Networks.hi fact,this kind of model might be called an infant protocol for DSS,which accepts final users raw data, integrates various sources of data,cleanses them from garbages,then normalizes them into an intermediatary data file.

我们在这里设计并实现了一个基于具有模糊式输出的人工神经网络的数据挖掘模型，这个模型实际上是一个具有智能的决策支持系统的雏形，能够对用户所给的原始数据进行处理，利用已经获得的知识对用户数据进行判断，并以适当的方式向用户解释系统决策的结果。

Compared with other data mining platforms,such as MS SQL2005,Oracle 10g, WEKA obviously has advantages in supporting machine learning algorithms. WEKA has provided almost all kinds of machine learning algorithms and implemented in JAVA. But WEKA has a lot of disadvantages for data minging.

与其他主流挖掘平台相比，WEKA机器学习平台在支持机器学习模式识别算法方面具有明显优势，WEKA提供了目前所有主要机器学习算法的JAVA实现，但其直接用于数据挖掘还有很多不足。

At last,presents a modem long - distance education model which establishes on the basis of Web mining and data mining .

在Web挖掘和数据挖掘研究的基础上，提出了一个智能化、个性化的现代远程教育系统结构模型。

On the other hand, the more important thing is because the urban housing is a kind of heterogeneity products.

另一方面，更重要的是由于城市住房是一种异质性产品。

Climate histogram is the fall that collects place measure calm value, cent serves as cross axle for a few equal interval, the area that the frequency that the value appears according to place is accumulated and becomes will be determined inside each interval, discharge the graph that rise with post, also be called histogram.

气候直方图是将所收集的降水量测定值，分为几个相等的区间作为横轴，并将各区间内所测定值依所出现的次数累积而成的面积，用柱子排起来的图形，也叫做柱状图。