Abstract
In this paper we describe a principled approach to explore the fitness-complexity trade-off using several optimality criteria together with a fuzzy model reduction technique based on the singular value decomposition (SVD). The role of these optimality criteria in fuzzy modeling is discussed and their practical applicability is illustrated using a nonlinear system modeling example.
| Original language | English (US) |
|---|---|
| Title of host publication | Mexico-USA Collaboration in Intelligent Systems Technologies |
| Editors | Anon |
| Publisher | IEEE |
| Pages | 394-402 |
| Number of pages | 9 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 1st Joint Conference on Intelligent Systems/ISAI/IFIS - Cancun, Mex Duration: Nov 12 1996 → Nov 15 1996 |
Other
| Other | Proceedings of the 1996 1st Joint Conference on Intelligent Systems/ISAI/IFIS |
|---|---|
| City | Cancun, Mex |
| Period | 11/12/96 → 11/15/96 |
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All Science Journal Classification (ASJC) codes
- Engineering(all)
Cite this
}
Constructing optimal fuzzy models using statistical information criteria. / Yen, John; Wang, Liang.
Mexico-USA Collaboration in Intelligent Systems Technologies. ed. / Anon. IEEE, 1996. p. 394-402.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Constructing optimal fuzzy models using statistical information criteria
AU - Yen, John
AU - Wang, Liang
PY - 1996
Y1 - 1996
N2 - In this paper we describe a principled approach to explore the fitness-complexity trade-off using several optimality criteria together with a fuzzy model reduction technique based on the singular value decomposition (SVD). The role of these optimality criteria in fuzzy modeling is discussed and their practical applicability is illustrated using a nonlinear system modeling example.
AB - In this paper we describe a principled approach to explore the fitness-complexity trade-off using several optimality criteria together with a fuzzy model reduction technique based on the singular value decomposition (SVD). The role of these optimality criteria in fuzzy modeling is discussed and their practical applicability is illustrated using a nonlinear system modeling example.
UR - http://www.scopus.com/inward/record.url?scp=0030364421&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0030364421&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0030364421
SP - 394
EP - 402
BT - Mexico-USA Collaboration in Intelligent Systems Technologies
A2 - Anon, null
PB - IEEE
ER -