Name
Abstract | ||
|---|---|---|
This paper presents a survey about different types of fuzzy information measures. A number of schemes have been proposed to combine the fuzzy set theory and its application to the entropy concept as a fuzzy information measurements. The entropy concept, as a relative degree of randomness, has been utilized to measure the fuzziness in a fuzzy set or system. However, a major difference exists between the classical Shannon entropy and the fuzzy entropy. In fact while the later deals with vagueness and ambiguous uncertainties, the former tackles probabilistic uncertainties (randomness) |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/FUZZ.2001.1008855 | Fuzzy Systems, 2001. The 10th IEEE International Conference |
Keywords | Field | DocType |
entropy,fuzzy set theory,information theory,Shannon entropy,fuzziness,fuzzy entropy,fuzzy information measures,fuzzy set theory,randomness,vagueness | Fuzzy classification,Fuzzy set operations,Computer science,Fuzzy measure theory,Fuzzy mathematics,Information diagram,Joint entropy,Artificial intelligence,Type-2 fuzzy sets and systems,Fuzzy number,Machine learning | Conference |
Volume | Citations | PageRank |
3 | 30 | 1.37 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salah al-Sharhan | 1 | 106 | 13.21 |
| Fakhri Karray | 2 | 1733 | 130.97 |
| Gueaieb, W. | 3 | 52 | 5.17 |
| Otman Basir | 4 | 435 | 31.33 |