Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Zhang, Gangqianga | Li, Zhaowenb; * | Zhang, Pengfeic | Xie, Ningxina
Affiliations: [a] School of Artificial Intelligence, Guangxi University for Nationalities, Nanning, Guangxi, P.R. China | [b] Key Laboratory of Complex System Optimization and Big Data Processing inDepartment of Guangxi Education, Yulin Normal University, Yulin, Guangxi, P.R. China | [c] Institute of Artificial Intelligence, School of Information Science and Technology, Southwest Jiaotong University, Chengdu, P.R. China
Correspondence: [*] Corresponding author. Zhaowen Li, Key Laboratory of Complex System Optimization and Big Data Processing in Department of Guangxi Education, Yulin Normal University, Yulin, Guangxi 537000, P.R. China. E-mail: [email protected].
Abstract: An information system as a database that stands for relationships between objects and attributes is an important mathematical model. An image information system is an information system where each of its information values is an image and its information structures embody internal features of this type of information system. Uncertainty measurement is an effective tool for evaluation. This paper explores measures of uncertainty for an information system by using the proposed information structures. The distance between two objects in an image information system is first given. After that, the fuzzy Tcos-equivalence relation, induced by this system by using Gaussian kernel method, is obtained, where Gaussian kernel is based on this distance. Next, information structures of this system are described by set vectors, dependence between information structures is studied and properties of information structures are given by using inclusion degree, and application for information structures and uncertainty measures of an image information system are investigated by the information structures. Moreover, effectiveness analysis is done to show the feasibility of the proposed measures from the angle of statistics. Finally, an application of the proposed measurement for attribute reduction is given. These results will be helpful for understanding the essence of uncertainty in an image information system.
Keywords: Granular computing, image information system, distance, information structure, dependence, inclusion degree, uncertainty, measure
DOI: 10.3233/JIFS-191628
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 295-317, 2021
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]