Information structures in an incomplete real-valued information system

被引：0

作者：

Zeng, Jiasheng ^{[1
]}

He, Jiali ^{[2
]}

Chen, Rongping ^{[1
]}

机构：

[1] Hunan Univ Commerce, Sch Math & Stat, Changsha, Hunan, Peoples R China

[2] Yulin Normal Univ, Sch Math & Stat, Yulin 537000, Peoples R China

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2019年 / 36卷 / 06期

关键词：

Granular computing; Incomplete real-valued information system; Gaussian kernel; Information granule; Information structure; Dependence; Inclusion degree; Information structures; UNCERTAINTY MEASURES; ATTRIBUTE REDUCTION; ROUGH; APPROXIMATION; GRANULATION; RULES; MODEL; SETS;

D O I：

10.3233/JIFS-181097

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An information system as a database that shows relationships between objects and attributes is a crucial mathematical model in the field of artificial intelligence. A real-valued information system is an information system where information function values of each attribute are real numbers. This paper explores information structures in an incomplete real-valued information system. Distances between two objects in a given subsystem of an incomplete real-valued information system is first constructed. Then, the fuzzy T-cos-equivalence relation, induced by this subsystem by using Gaussian kernel method, is obtained, where Gaussian kernel is based on this distance. Next, information structure of this subsystem is proposed. Moreover, relationships between two information structures are studied from the two aspects of dependence and separation. Finally, the dependence between two information structures is studied by using inclusion degree. These results will be helpful for establishing a framework of granular computing.

引用

页码：5305 / 5318

页数：14

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