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内逆P-信息智能融合与它的属性析取特征-应用

Internal Inverse P-information Intelligent Fusion and its Attribute Disjunctive Character Application

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【作者】 吴松丽陈桂友史开泉

【Author】 WU Song-li;CHEN Gui-you;SHI Kai-quan;School of Mathematics,Shandong University;School of Control Science and Engineering,Shandong University;

【机构】 山东大学数学学院山东大学控制科学与工程学院

【摘要】 逆P-集合(inverse packet set)是由内逆P-集合珡XF(internal inverse packet set)与外逆P-集合珡X珚F(outer inverse packet set)构成的元素集合对;或者,(珡XF,珡X珚F)是逆P-集合;逆P-集合具有动态特性。利用内逆P-集合与内逆P-推理(internal inverse packet reasoning)、内逆P-信息智能融合生成、内逆P-信息智能融合补充生成与内逆P-信息智能融合度量,给出内逆P-信息智能融合定理、内逆P-信息智能融合依赖定理与内逆P-信息智能融合还原定理。给出内逆P-信息智能融合的属性析取特征与属性析取扩展定理,以及属性析取扩展-未知内逆P-信息智能融合发现原理;给出这些理论结果的应用。逆P-集合是研究另一类动态信息应用的新理论、新方法;另一类动态信息具有属性析取特征。

【Abstract】 Inverse P-sets(packet sets)are a pair of element sets composed of internal inverse P-set珡XF(internal inverse packet set珡XF)and outer inverse P-set珡X珚F(outer inverse packet set珡X珚F),or(珡XF,珡X珚F)is an inverse P-set.Inverse P-set has dynamic characteristic.Using internal P-set,internal inverse P-reasoning(internal inverse packet reasoning),internal inverse P-information intelligent fusion generation,internal inverse P-information intelligent fusion supplemented generation and internal inverse P-information intelligent fusion measurement,internal inverse P-information intelligent fusion theorem,internal inverse P-information intelligent fusion dependent theorem and internal inverse P-information intelligent fusion recovery theorem were proposed.The attribute disjunctive character and attribute disjunctive expansion theorem of internal inverse P-information intelligent fusion,the attribute disjunctive expansion and unknown internal inverse P-information intelligent fusion discovery theorem recovery theorem were put forward.The application of these theory results was presented.Inverse P-sets is a new theorem and method of studying the other dynamic information application.The dynamic information has attribute disjunctive character.

【基金】 国家自然科学基金项目(61273277);福建省自然科学基金项目(2013J01028);河南省基础与前沿技术研究计划资助项目(132300410289)资助
  • 【文献出处】 计算机科学 ,Computer Science , 编辑部邮箱 ,2014年01期
  • 【分类号】O144
  • 【被引频次】4
  • 【下载频次】37
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