摘要
在社会和自然现象中存在着大量的混沌模式，相应地，在用来表示这些现象的数据库中同样也存在着混沌模式．一般在ＫＤＤ中，混沌模式经常出现在确定模式与纯噪声关系之间，表现出很大的随机性，因此都将其作为随机噪声关系而忽略．该文通过使用Ｊ．Ｚｙｔｋｏｗ的基于统计分析的Ｆｏｒｔｙ－Ｎｉｎｅｒ方法说明了这一点．通过对混沌模式的分析，提出了一种混沌模式发现的网络方法．该方法不仅能判断数据库中是否存在混沌模式，而且能有效地描述和预测该混沌模式．另外，该算法非常适合处理大型数据库，在当今活跃的ＫＤＤ研究领域中具有广泛的应用前景．
There exists a lot of chaotic patterns in the natural kingdom and social society. Databases recording this kind of data also contain the chaotic patterns. Generally, the chaotic patterns are characteristics of greatly random fluctuation although they often appear between deterministic and stochastic patterns in KDD. Therefore, the chaotic patterns are always treated as random fluctuation distributions and are ignored. Such viewpoint illustrated by J.Zytkow's Forty Niner is that a pattern discovery platform based on statistics. A new network method to discover chaotic pattern in databases is proposed in this paper. This method together with the Forty Niner can not only discover the chaotic pattern, but also forecast it efficiently. In addition, this method is very suitable to deal with large databases and has extensive applicable prospects in the vivid researching fields of KDD.
出处
《软件学报》
EI
CSCD
北大核心
1999年第5期469-474,共6页
Journal of Software
基金
国家自然科学基金
国家863高科技项目基金
关键词
KDD
模式发现
预测
混沌模式
数据库
知识发现
KDD (knowledge discovery in databases), pattern discovery and forecasting, chaotic pattern, chaotic pattern discovery networks.
