Abstract
The Shannon entropy measures conflict in probabilistic evidence. Evidence Theory also presents information that is inherently conflicting. Uncertainty measures for conflict in Evidence Theory include aggregate uncertainty, dissonance, confusion, discord, granularity and strife. This paper compares and critiques the properties of these measures.
| Original language | English |
|---|---|
| Title of host publication | Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS |
| Editors | M.H. Smith, W.A. Gruver, L.O. Hall |
| Pages | 1741-1745 |
| Number of pages | 5 |
| Volume | 3 |
| State | Published - 2001 |
| Event | Joint 9th IFSA World Congress and 20th NAFIPS International Conference - Vancouver, BC, Canada Duration: Jul 25 2001 → Jul 28 2001 |
Other
| Other | Joint 9th IFSA World Congress and 20th NAFIPS International Conference |
|---|---|
| Country | Canada |
| City | Vancouver, BC |
| Period | 7/25/01 → 7/28/01 |
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Media Technology
Fingerprint Dive into the research topics of 'Measuring conflict in evidence theory'. Together they form a unique fingerprint.
Cite this
Wierman, M. J. (2001). Measuring conflict in evidence theory. In M. H. Smith, W. A. Gruver, & L. O. Hall (Eds.), Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS (Vol. 3, pp. 1741-1745)