基于时间序列的数据挖掘在证券中的应用

为更好地对股票数据进行分析，从理论上对数据挖掘中时间序列的产生、应用进行了研究，通过对时间序列处理以及相关性搜索的多种方法的比较和分析，设计一个以股票预测为对象的小型系统。该系统首先对时间序列进行适当的处理，然后进行相似性搜索，分析未来的短时间的走势是否是历史上的重现。同时对得到的结果进行了分析，实验结果表明，该方法能找到股票数据中历史上相似走势，并通过历史走势分析当前的走势。

Application of Time Series Data Mining on Security Analysis

For better analysis of stock exchange data, we give a brief introduction of the generation and application of time series in data mining and by comparison and analysis of different ways of time series processing and relevance searching, we choose a reasonable method to design a small system which is used for stock forcasting. First, the time series are processed properly and the similarity search is preformed and then analyse whether the short term trend is the resurgence of history. The final result is anlysised. Experiments showed that the method can find the similarity trends of the stock exchange data in history, and by analyzing similarity trends in history, current trend can be predicted.