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 |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Media Technology
Cite this
Measuring conflict in evidence theory. / Wierman, Mark J.
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS. ed. / M.H. Smith; W.A. Gruver; L.O. Hall. Vol. 3 2001. p. 1741-1745.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Measuring conflict in evidence theory
AU - Wierman, Mark J.
PY - 2001
Y1 - 2001
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0035792038&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0035792038&partnerID=8YFLogxK
M3 - Conference contribution
VL - 3
SP - 1741
EP - 1745
BT - Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
A2 - Smith, M.H.
A2 - Gruver, W.A.
A2 - Hall, L.O.
ER -