《山东大学学报(理学版)》 ›› 2019, Vol. 54 ›› Issue (2): 1-29.

• •

### 大数据结构-逻辑特征与大数据规律

1. 山东大学数学学院, 山东 济南 250100
• 发布日期:2019-02-25
• 作者简介:史开泉(1945— ), 男, 教授, 博士生导师, 研究方向为数据智能系统理论与应用. E-mail:shikq@sdu.edu.cn
• 基金资助:
山东省自然科学基金资助项目(zr2013aq019);福建省自然科学基金资助项目(2015J05010)

### Big data structure-logic characteristics and big data law

SHI Kai-quan

1. School of Mathematics, Shandong University, Jinan 250100, Shandong, China
• Published:2019-02-25

Abstract: P-sets, inverse P-sets are two models obtained by introducing dynamic features into a finite ordinary set X and improving the set X. By using P-sets, inverse P-sets and their dynamic and logical features, ∧-type big data structure and its generation with attribute conjunction extension-contraction feature, ∨-type big data structure and its generation with attribute disjunctive extension-contraction feature, and∧-∨type big data structure and its generation of the mixture of ∧-type big data and ∨-type big data are given respectively. The fusion and its generation of big data and the intelligent mining theorems of big data fusion are given. Granulation characteristics and granulation filtration theorems of big data are given. The heredity and its generation of big data, and heredity intelligence separation and separation theorem of big data are given. Big data hiding-camouflage and intelligent generation under the inference condition of P-augmented matrix, and big data hiding-camouflage theorems are given. The model and method of big data law generation, and the state of big data law are given. By using the state of big data law, the risk estimation of investment-profit big data is given.

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