Uncertainty measures in ordered information system based on approximation operators
type: Item
instance of: scholarly article
title: Uncertainty measures in ordered information system based on approximation operators
zbMATH Open document ID: 1474.68355
DOI: 10.1155/2014/846205
author: Bingjiao Fan
author: Jianhang Yu
author: Weihua Xu
published in: Abstract and Applied Analysis
publication date: 2019-02-14T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 68T37
zbMATH DE Number: 7023187
Wikidata QID: Q59041994
describes a project that uses: LERS
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/846205
OpenAlex ID: W2009723748
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description: scientific article; zbMATH DE number 7023187