Uncertainty Measures in Ordered Information System Based on Approximation Operators

Bingjiao Fan, Weihua Xu and Jianhang Yu

Abstract and Applied Analysis, 2014, vol. 2014, 1-17

Abstract:

This paper focuses on constructing uncertainty measures by the pure rough set approach in ordered information system. Four types of definitions of lower and upper approximations and corresponding uncertainty measurement concepts including accuracy, roughness, approximation quality, approximation accuracy, dependency degree, and importance degree are investigated. Theoretical analysis indicates that all the four types can be used to evaluate the uncertainty in ordered information system, especially that we find that the essence of the first type and the third type is the same. To interpret and help understand the approach, experiments about real-life data sets have been conducted to test the four types of uncertainty measures. From the results obtained, it can be shown that these uncertainty measures can surely measure the uncertainty in ordered information system.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/AAA/2014/846205.pdf (application/pdf)
http://downloads.hindawi.com/journals/AAA/2014/846205.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:846205

DOI: 10.1155/2014/846205

Access Statistics for this article

More articles in Abstract and Applied Analysis from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().