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J4 ›› 2013, Vol. 48 ›› Issue (8): 97-103.

• 论文 • 上一篇    下一篇

逆P-集合与信息智能融合挖掘-发现

郭华龙,陈保会*,汤积华   

  1. 龙岩学院数学与计算机科学学院, 福建 龙岩 364012
  • 收稿日期:2012-10-22 出版日期:2013-08-20 发布日期:2013-08-21
  • 通讯作者: 陈保会(1983- ), 男, 讲师,硕士,研究方向为信息系统与系统识别. Email: sdtonychen@yahoo.cn
  • 作者简介:郭华龙(1977- ), 男, 讲师,硕士,研究方向为软件工程、信息系统与系统识别. Email:ly_ghl@126.com
  • 基金资助:

    福建省教育厅A类科技项目(JA09231,JA10257);福建省龙岩市科技局项目 (2011LY20)

Inverse P-sets and intelligent fusion mining-discovery of information

GUO Hua-long, CHEN Bao-hui*, TANG Ji-hua   

  1. School of Mathematics and Computer Sciences, Longyan University, Longyan 364012, Fujian, China
  • Received:2012-10-22 Online:2013-08-20 Published:2013-08-21

摘要:

 逆P-集合是一个新的动态数学模型, 它是把动态特性引入到有限普通集合X内, 改进有限普通集合X被提出的。逆P-集合是由内逆P-集合F与外逆P-集合构成的元素集合对。或者, (F,)是逆P-集合, 逆P-集合具有动态特性。在一定的条件下, 逆P-集合被还原成有限普通集合。逆P-集合具有P-集合相反的动态特性。逆P-推理是逆P-集合生成的一个动态推理。利用逆P-集合, 逆P-推理, 本文给出信息智能融合生成, 信息智能融合度概念, 给出信息智能融合挖掘-发现与信息智能融合挖掘-发现定理, 给出挖掘-发现准则。最后,利用这些结果给出信息智能融合挖掘-发现的应用。

关键词: 逆P-集合; 逆P-推理; 信息智能融合; 挖掘-发现; 挖掘-发现定理; 挖掘-发现准则

Abstract:

Inverse packet sets is a new dynamic mathematical model, which is presented by introducing dynamic characteristics into Cantor set and improving Cantor set theory. Inverse packet sets is composed of internal inverse P-sets and outer inverse P-sets, and it is a set pair, i.e., (F,) a inverse packet sets, which has dynamic characteristic. In certain conditions, the inverse packet sets can be reduced into a finite general set. It has opposite dynamic characteristics to packet sets. Inverse packet reasoning is a dynamic reasoning generated by inverse packet sets. Based on inverse packet sets and inverse packet reasoning, the concepts of intelligent fusion generation of information and the intelligent fusion degree of information are put forward. The mining-discovery theorem of intelligent fusion of information and the mining-discovery criterion are given. Using those results, the application to intelligent fusion mining-discovery of information is proposed.

Key words: inverse packet sets; inverse packet reasoning; intelligent fusion of information; mining-discovery; mining-discovery theorem; mining-discovery criterion

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