P-增广矩阵与信息的智能动态发现-辨识

利用普通增广矩阵概念与P-集合动态结构交叉,改进普通增广矩阵概念,提出P-增广矩阵,给出P-增广矩阵结构;P-增广矩阵由内P-增广矩阵与外P-增广矩阵共同构成。给出内P-增广矩阵属性定理,外P-增广矩阵属性定理与P-增广矩阵属性定理;给出P-增广矩阵与普通增广矩阵的还原关系。改进P-推理,提出P-增广矩阵推理,给出推理结构;P-增广矩阵推理由内P-增广矩阵推理与外P-增广矩阵推理共同构成。提出属性的P-增广合取范式,给出属性的P-增广合取范式与属性的普通合取范式的关系,提出属性的P-增广合取范式还原定理;给出满足P-增广矩阵推理条件的信息的智能动态发现-辨识定理,最后给出了应用。

P-augmented matrix and dynamic intelligent discovery-identification of information

By improving ordinary augmented matrix and crossing the concept of ordinary augmented matrix and the dynamic structure of P-sets, P-augmented matrix is proposed,and its structure is also given. P-augmented matrix consists of internal P-augmented matrix and outer P-augmented matrix. Then the attribute theorems of internal P-augmented matrix, outer P-augmented matrix and P-augmented matrix are obtained. The reduction relationships between P-augmented matrix and ordinary augmented matrix are given. By improving P-inference, P-augmented matrix inference is proposed, and its inference structure is given. P-augmented matrix inference consists of internal P-augmented matrix inference and outer P-augmented matrix inference. Then P-augmented conjunctive normal form of attribute is proposed, and the relationships between P-augmented conjunctive normal form of attribute and ordinary conjunctive normal form of attribute are given. The reduction theorems of P-augmented conjunctive normal form of attribute and dynamic intelligent discovery-identification of information that satisfy the antecedent of P-augmented matrix inference are proposed. Finally, an application is shown.