数据融合和数据挖掘都属于数据处理技术,但以往的研究者很少将两者结合起来。实际上两者是密切相关的,两者都服务于知识发现这一目标。数据融合的目的是形成数据挖掘的数据基础,数据挖掘的目的是在这一数据基础上提取有用的知识,完成知识发现。因此,我们的研究目标是把两者结合起来,在数据融合的基础上,以人工智能理论和Bayes方法为主,设计有效算法进行数据挖掘,以尽可能多的发掘环境监测数据中的有效信息。 Both data fusion and data mining are data processing techniques, but historians rarely combine the two. In fact the two are closely related, both serving the goal of knowledge discovery. The purpose of data fusion is to form the data foundation of data mining. The purpose of data mining is to extract useful knowledge and complete knowledge discovery based on this data. Therefore, our research goal is to combine the two. On the basis of data fusion, artificial intelligence theory and Bayes method are the main topics. We design effective algorithms for data mining to explore as much as possible of effective information in environmental monitoring data .