How the learning of rule weights affects the interpretability of fuzzy systems

1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence

Volumn 2, Issue , 1998, Pages 1235-1240

  Nauck, Detlef ^a   Kruse, Rudolf ^a  

^a OTTO VON GUERICKE UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY SETS; LEARNING SYSTEMS; MATHEMATICAL MODELS; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS;

RULE WEIGHTS;

FUZZY CONTROL;

EID: 0031627851     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.1998.686295     Document Type: Conference Paper

References (12)

1. Didier Dubois, Jerome Lang, and Henri Prade. Automated reasoning using possibilistic logic: Semantics, belief revision and variable certainty weights. In Proc. 5th Workshop on Uncertainty in Artificial Intelligence, pages 81-87, Ontario, 1989. Windsor.
2. Didier Dubois and Henri Prade, editors. Possibility Theory. Plenum Press, New York, 1988.
3. R.A. Fisher. The use of multiple measurements in tax-onomic problems. Annual Eugenics, 7(Part II):179-188, 1936.
4. Saman K. Halgamuge and Manfred Glesner. Neural networks in designing fuzzy systems for real world applications. Fuzzy Sets and Systems, 65:1-12, 1994.
5. D.E. Heckerman. Probabilistic interpretation for mycin's certainty factors. In J.F. Lemmer and L.N. Kanal, editors, Uncertainty in Artificial Intelligence (2), pages 167-196. North-Holland, Amsterdam, 1988.
6. Bart Kosko. Neural Networks and Fuzzy Systems. A Dynamical Systems Approach to Machine Intelligence. Prentice Hall, Englewood Cliffs, NJ, 1992.
7. Rudolf Kruse, Jörg Gebhardt, and Frank Klawonn. Foundations of Fuzzy Systems. Wiley, Chichester, 1994.
8. Rudolf Kruse, Erhard Schwecke, and Jochen Heinsohn. Uncertainty and Vagueness in Knowledge-Based Systems: Numerical Methods. Springer-Verlag, Berlin, 1991.
9. Detlef Nauck, Prank Klawonn, and Rudolf Kruse. Foundations of Neuro-Fuzzy Systems. Wiley, Chichester, 1997.
10. Detlef Nauck and Rudolf Kruse. A neuro-fuzzy method to learn fuzzy classification rules from data. Fuzzy Sets and Systems, 89:277-288, 1997.
11. Detlef Nauck and Rudolf Kruse. New learning strategies for NEFCLASS. In Proc. Seventh International Fuzzy Systems Association World Congress IFSA'97, volume IV, pages 5055, Prague, 1997.
12. Detlef Nauck, Ulrike Nauck, and Rudolf Kruse. Generating classification rules with the neuro-fuzzy system NEFCLASS. In Proc. Biennial Conference of the North American Fuzzy Information Processing Society NAFIPS'96, Berkeley, CA, June 1996.