Name
Abstract | ||
|---|---|---|
In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in literature. Some examples illustrate the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/s00500-006-0146-7 | Soft Comput. |
Keywords | Field | DocType |
Fuzzy system identification,Fuzzy clustering,Interpretability,Local models | Data mining,Fuzzy clustering,Fuzzy classification,Computer science,Fuzzy set operations,Artificial intelligence,FLAME clustering,Fuzzy number,Cluster analysis,Mathematical optimization,Defuzzification,Correlation clustering,Algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
11 | 10 | 1432-7643 |
Citations | PageRank | References |
3 | 0.48 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. L. Díez | 1 | 3 | 0.82 |
| J. L. Navarro | 2 | 3 | 0.48 |
| A. Sala | 3 | 562 | 33.44 |