Abstract
The theory of Cloud sets is presented and standard techniques of set theory allow for the development of a rich algebra of cloud sets. When measures are added we can introduce the Cloud complement and show that Cloud Sets are isomorphic to fuzzy sets. However, the fundamental manipulations, techniques, and definitions are simpler and more amenable to analysis. For example, the extension principle is easy to define.
| Original language | English |
|---|---|
| Title of host publication | 2010 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2010 |
| DOIs | |
| State | Published - 2010 |
| Event | 2010 Annual North American Fuzzy Information Processing Society Conference, NAFIPS'2010 - Toronto, ON, Canada Duration: Jul 12 2010 → Jul 14 2010 |
Other
| Other | 2010 Annual North American Fuzzy Information Processing Society Conference, NAFIPS'2010 |
|---|---|
| Country | Canada |
| City | Toronto, ON |
| Period | 7/12/10 → 7/14/10 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Mathematics(all)
Cite this
Cloud sets as a measure theoretic basis for fuzzy set theory. / Wierman, Mark J.
2010 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2010. 2010. 5548268.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Cloud sets as a measure theoretic basis for fuzzy set theory
AU - Wierman, Mark J.
PY - 2010
Y1 - 2010
N2 - The theory of Cloud sets is presented and standard techniques of set theory allow for the development of a rich algebra of cloud sets. When measures are added we can introduce the Cloud complement and show that Cloud Sets are isomorphic to fuzzy sets. However, the fundamental manipulations, techniques, and definitions are simpler and more amenable to analysis. For example, the extension principle is easy to define.
AB - The theory of Cloud sets is presented and standard techniques of set theory allow for the development of a rich algebra of cloud sets. When measures are added we can introduce the Cloud complement and show that Cloud Sets are isomorphic to fuzzy sets. However, the fundamental manipulations, techniques, and definitions are simpler and more amenable to analysis. For example, the extension principle is easy to define.
UR - http://www.scopus.com/inward/record.url?scp=77956577546&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77956577546&partnerID=8YFLogxK
U2 - 10.1109/NAFIPS.2010.5548268
DO - 10.1109/NAFIPS.2010.5548268
M3 - Conference contribution
SN - 9781424478576
BT - 2010 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2010
ER -