大数据分解-融合及其智能获取  

Big Data Decomposition-Fusion and Its Intelligent Acquisition

作　　者：刘纪芹 史开泉[2] LIU Ji-qin;SHI Kai-quan(School of Mathematics and Quantitative Economics,Shandong University of Finance and Economics,Jinan 250014,China;School of Mathematics,Shandong University,Jinan 250100,China)

机构地区：[1]山东财经大学数学与数量经济学院,济南250014 [2]山东大学数学学院,济南250100

出　　处：《计算机科学》2020年第6期66-73,共8页Computer Science

基　　金：国家社会科学基金项目(71663010);山东省自然科学基金项目(zr2013aq019)。

摘　　要：文中给出了通过大数据分解、融合生成的大数据分解-融合以及大数据距离;利用这些概念,给出了大数据并-交分解定理以及大数据交-并分解定理与它们的属性合取关系、大数据融合的智能生成定理与大数据融合的距离关系、大数据分解-融合的识别准则与大数据分解-融合获取的智能算法与算法的过程,以及这些理论结果在大数据分解-融合智能获取的应用。文中给出了∧型大数据新的特征,∧型大数据是利用P-集合模型得到的。The concepts of big data decomposition-fusion and big data distance generated by big data decomposition and fusion are given.By using these concepts,an union-intersection decomposition theorem of big data,an intersection-union decomposition theorem of big data and their attribute conjunction relation are given.Intelligent generation theorems and the distance relationship of big data fusion are given.A recognition criterion of big data decomposition-fusion,an intelligent algorithm and algorithm process of big data decomposition-fusion acquisition are given.The application of these theoretical results in big data decomposition-fusion intelligent acquisition is presented.In this paper,the new characteristics of∧-type big data are given,∧-type big data is obtained by using P-sets model.

关 键 词：大数据 分解-融合 识别准则 智能算法 

分 类 号：O144[理学—数学] TP391[理学—基础数学]