Name
Abstract | ||
|---|---|---|
Interval-valued information systems are generalized models of single-valued information systems. Accuracy and roughness are employed to depict the uncertainty of a set under an attribute subset in a Pawlak rough set model based on equivalence classes. Information-theoretic measures of uncertainty for rough sets have also been proposed. However, there are few studies on uncertainty measurements for interval-valued information systems. This paper addresses the uncertainty measurement problem in interval-valued information systems. The concept of the similarity degree, based on the possible degree, is introduced. Consequently, the similarity relation between two interval objects are constructed by a given similarity rate θ. Based on the similarity relation, θ-similarity classes are defined. Under this definition, θ-accuracy and θ-roughness are given for interval-valued information systems, which are generalizations of the concepts accuracy and roughness for the equivalence relation-based rough set model. Moreover, an alternative uncertainty measure, called the θ-rough degree, is proposed. Theoretical studies and numerical experiments show that the proposed measures are effective and suitable for interval-valued information systems. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.ins.2013.06.047 | Information Sciences |
Keywords | Field | DocType |
Interval data,Uncertainty measure,Rough set theory,Interval-valued information systems,Similarity degree,Roughness | Information system,Discrete mathematics,Equivalence relation,Generalization,Measurement uncertainty,Sensitivity analysis,Uncertainty analysis,Rough set,Equivalence class,Mathematics | Journal |
Volume | Issue | ISSN |
251 | null | 0020-0255 |
Citations | PageRank | References |
20 | 0.56 | 53 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianhua Dai | 1 | 896 | 51.62 |
| Wentao Wang | 2 | 222 | 5.52 |
| Ju-Sheng Mi | 3 | 2054 | 77.81 |