幂拓扑分子格的积

引入形如（Ｌ＾Ｘ，η）的拓扑分子格（称为幂拓扑分子格）族的“Ｘ积”和“积”以及幂扑分子格的“核”（核是分明拓扑空间），证明了幂拓扑分子格的分明性、弱诱导必和弱层性积性和可积性，对弱诱导的幂拓年分子格式，积之核等于核之积。     

弱诱导性不是Fuzzy同胚不变性

将文［１］中的ＬＦ拓扑空间的满层性、北诱导性、可拓扑生成性推广到形如（Ｌ＾ｘ，η）的幂拓扑分子格中，证明了满层性是Ｆｕｚｚｙ同胚不变性；弱诱导性不是Ｆｕｚｚｙ同胚不变性，是双诱导同胚不变性。     

布尔关联规则集的结构

由事物数据库的项目集构造一个分层偏序集,使所有布尔关联规则之集构成该分层偏序集的一个下集.本文讨论了该下集的极大元及其性质.     

Mining Maximal Frequent Patterns in a Unidirectional FP-tree

Becausemining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model only finds out the maximal frequent patterns, which can generate all frequent patterns. FP-growth algorithm is one of the most efficient frequent-pattern mining methods published so far. However,because FP-tree and conditional FP-trees must be two-way traversable, a great deal memory is needed in process of mining. This paper proposes an efficient algorithm Unid_FP-Max for mining maximal frequent patterns based on unidirectional FP-tree. Because of generation method of unidirectional FP-tree and conditional unidirectional FP-trees, the algorithm reduces the space consumption to the fullest extent. With the development of two techniques：single path pruning and header table pruning which can cut down many conditional unidirectional FP-trees generated recursively in mining process, Unid_ FP-Max further lowers the expense of time and space.     

A Depth-first Algorithm of Finding All Association Rules Generated by a Frequent Itemset

The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree （GRSET） which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents.Experiments show GRSET algorithm to be practicable and efficient.     

基于小波变换和升高变换的IC图像纹理分割算法

引入二值图像的升高变换,并结合小波变换提出一种IC图像纹理分割算法．在纹理分割过程中,首先对IC图像进行小波分解并对二值化后的近视部分进行升高变换,然后利用原图像信息识别出不同纹理,分割出不同区域．实验表明,该算法快速、高效,具有很好的实用性．