| 2007 |
|---|
| 6 | EE | Tamas Kenesei,
Johannes A. Roubos,
János Abonyi:
A Combination-of-Tools Method for Learning Interpretable Fuzzy Rule-Based Classifiers from Support Vector Machines.
IDEAL 2007: 477-486 |
| 2003 |
|---|
| 5 | EE | Johannes A. Roubos,
Magne Setnes,
János Abonyi:
Learning fuzzy classification rules from labeled data.
Inf. Sci. 150(1-2): 77-93 (2003) |
| 4 | EE | János Abonyi,
Johannes A. Roubos,
Ferenc Szeifert:
Data-driven generation of compact, accurate, and linguistically sound fuzzy classifiers based on a decision-tree initialization.
Int. J. Approx. Reasoning 32(1): 1-21 (2003) |
| 2001 |
|---|
| 3 | EE | Fernando Jiménez,
Antonio F. Gómez-Skarmeta,
Johannes A. Roubos,
Robert Babuska:
Accurate, Transparent, and Compact Fuzzy Models for Function Approximation and Dynamic Modeling through Multi-objective Evolutionary Optimization.
EMO 2001: 653-667 |
| 2 | | János Abonyi,
Johannes A. Roubos,
Marcel Oosterom,
Ferenc Szeifert:
Compact TS - Fuzzy Models Through Clustering and OLS Plus FIS Model Reduction.
FUZZ-IEEE 2001: 1420-1423 |
| 1999 |
|---|
| 1 | EE | Johannes A. Roubos,
Stanimir Mollov,
Robert Babuska,
Henk B. Verbruggen:
Fuzzy model-based predictive control using Takagi-Sugeno models.
Int. J. Approx. Reasoning 22(1-2): 3-30 (1999) |
