Abstract
A new measure of uncertainty for evidence theory is presented. The measure of granularity is similar in form to the Shannon entropy but depends on set size as well as weight. It also has connections to the Hartley measure and the granularity measure of rough set theory.
| Original language | English |
|---|---|
| Pages (from-to) | 649-660 |
| Number of pages | 12 |
| Journal | International Journal of General Systems |
| Volume | 30 |
| Issue number | 6 |
| State | Published - 2001 |
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All Science Journal Classification (ASJC) codes
- Computational Theory and Mathematics
- Theoretical Computer Science
- Control and Systems Engineering
- Information Systems
- Computer Science Applications
- Modeling and Simulation
Cite this
Measuring granularity in evidence theory. / Wierman, Mark J.
In: International Journal of General Systems, Vol. 30, No. 6, 2001, p. 649-660.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Measuring granularity in evidence theory
AU - Wierman, Mark J.
PY - 2001
Y1 - 2001
N2 - A new measure of uncertainty for evidence theory is presented. The measure of granularity is similar in form to the Shannon entropy but depends on set size as well as weight. It also has connections to the Hartley measure and the granularity measure of rough set theory.
AB - A new measure of uncertainty for evidence theory is presented. The measure of granularity is similar in form to the Shannon entropy but depends on set size as well as weight. It also has connections to the Hartley measure and the granularity measure of rough set theory.
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UR - http://www.scopus.com/inward/citedby.url?scp=0013440283&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:0013440283
VL - 30
SP - 649
EP - 660
JO - International Journal of General Systems
JF - International Journal of General Systems
SN - 0308-1079
IS - 6
ER -