数据的动态挖掘与P-增广矩阵关系

P-增广矩阵是通过利用P-集合的结构与动态特征,改进普通增广矩阵A^*提出的。P-增广矩阵是由内P-增广矩阵A^(-overF)与外P-增广矩阵A^F构成的矩阵对,或者(A^(-overF),A^F)是P-增广矩阵。在一定条件下,P-增广矩阵(A^(-overF),A^F)被还原成普通增广矩阵A^*。利用P-增广矩阵的结构与动态特征,给出数据的动态挖掘研究及其与P-增广矩阵的关系。提出数据的动态挖掘的内P-增广矩阵判定定理,外P-增广矩阵判定定理与P-增广矩阵判定定理,给出数据的动态挖掘的P-增广矩阵准则,利用这些理论结果,给出一个简单应用。

Relationships between dynamic data mining and P-augmented matrix

P-augmented matrix is proposed by adopting the structures and dynamic characteristics of packet sets to improve ordinary augmented matrix A^*. P-augmented matrix consists of internal P-augmented matrix A^(-overF) and outer P-augmented matrix A^F, denoted by(A^(-overF),A^F). Under some certain conditions, P-augmented matrix can be reduced into ordinary augmented matrix A^*. By using the structures and dynamic characteristics of P-augmented matrix, the research of dynamic data mining is carried out. Several relationships, theorems and criterion are obtained as follows: the relationships between dynamic data mining and P-augmented matrix; the internal P-augmented matrix decision theorem, the outer P-augmented matrix decision theorem and the P-augmented matrix decision theorem for data dynamic mining; the P-augmented matrix criterion for dynamic data mining. Finally, these results are verified by an application.