数据库中混沌模式的发现和预测

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.

Discovery and Forecast of Chaotic Pattern in Databases

There exists a lot of chaotic patterns in the natural kingdom and social society. Databases recording this kind of data also c ontain 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 treat ed as random fluctuation distributions and are ignored. Such viewpoint illustra ted by J.Zytkow's Forty-Niner is that a pattern discovery platform based on st atistics. A new network method to discover chaotic pattern in databases is propo sed in this paper. This method together with the Forty-Niner can not only disco ver the chaotic pattern, but also forecast it efficiently. In addition, this met hod is very suitable to deal with large databases and has extensive applicable p rospects in the vivid researching fields of KDD.