Combining user's preferences and quality criteria into a new index for guiding the design of fuzzy systems with a good interpretability-accuracy trade-off

2010 IEEE World Congress on Computational Intelligence, WCCI 2010

Volumn , Issue , 2010, Pages

  Alonso, José M ^a   Magdalena, Luis ^a  

^a EUROPEAN CENTRE FOR SOFT COMPUTING   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATION PROCESS; DECISION LEVELS; DESIGN PROCESS; EXPERIMENTAL STUDIES; INTERPRETABILITY; MULTICRITERIA DECISION PROBLEM; NEW INDICES; ORDERED WEIGHTED AVERAGING OPERATOR; QUALITY CRITERIA; QUALITY INDICES;

AGGLOMERATION; ARTIFICIAL INTELLIGENCE; DECISION MAKING; FUZZY SETS; HIERARCHICAL SYSTEMS;

DECISION THEORY;

EID: 78549233036     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2010.5584767     Document Type: Conference Paper

References (41)

1. W. Pedrycz and F. Gomide, Fuzzy Systems Engineering: Toward Human-Centric Computing. Wiley-IEEE Press, 2007.
2. L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, pp. 338-353, 1965.
3. U. Bodenhofer and P. Bauer, "A formal model of interpretability of linguistic variables," In [8], pp. 524-545, 2003.
4. C. Mencar, G. Castellano, and A. M. Fanelli, "Some fundamental interpretability issues in fuzzy modeling," in Joint EUSFLAT-LFA, Barcelona, Spain, September, 7-9, 2005, pp. 100-105.
5. J. V. de Oliveira, "Semantic constraints for membership function optimization," IEEE Transactions on Systems, Man and Cybernetics. Part A, Systems and Humans, vol. 29, pp. 128-138, 1999.
6. C. Mencar and A. M. Fanelli, "Interpretability constraints for fuzzy information granulation," Information Sciences, vol. 178, pp. 4585-4618, 2008.
7. S. Guillaume, "Designing fuzzy inference systems from data: An interpretability-oriented review," IEEE Transactions on Fuzzy Systems, vol. 9, no. 3, pp. 426-443, 2001.
8. J. Casillas, O. Cordón, F. Herrera, and L. Magdalena, Interpretability issues in fuzzy modeling. Studies in Fuzziness and Soft Computing, Springer-Verlag, Heidelberg, 2003, vol. 128.
9. J. M. Alonso, L. Magdalena, and S. Guillaume, "HILK: A new methodology for designing highly interpretable linguistic knowledge bases using the fuzzy logic formalism," International Journal of Intelligent Systems, vol. 23, no. 7, pp. 761-794, 2008.
10. S.-M. Zhou and J. Q. Gan, "Low-level interpretability and highlevel interpretability: A unified view of data-driven interpretable fuzzy system modelling," Fuzzy Sets and Systems, vol. 159, pp. 3091-3131, 2008.
11. 3 fuzzy rule systems from data using evolution strategies," IEEE Transactions on Systems, Man, and Cybernetics, vol. 29, no. 6, pp. 829-845, 1999.
12. J. Casillas, O. Cordón, M. J. del Jesús, and F. Herrera, "Genetic tuning of fuzzy rule deep structures preserving interpretability and its interaction with fuzzy rule set reduction," IEEE Transactions on Fuzzy Systems, vol. 13, pp. 13-29, 2005.
13. R. Alcalá, J. Alcalá-Fdez, J. Casillas, O. Cordón, and F. Herrera, "Hybrid learning models to get the interpretability- accuracy trade-off in fuzzy modeling," Soft Computing, vol. 10, no. 9, pp. 717-734, 2006.
14. H. Ishibuchi and Y. Nojima, "Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning," International Journal of Approximate Reasoning, vol. 44, pp. 4-31, 2007.
15. E. V. Broekhoven, V. Adriaenssens, and B. D. Baets, " Interpretabilitypreserving genetic optimization of linguistic terms in fuzzy models for fuzzy ordered classification: An ecological case study," International Journal of Approximate Reasoning, vol. 44, pp. 65-90, 2007.
16. R. Alcalá, P. Ducange, F. Herrera, B. Lazzerini, and F. Marcelloni, "A multi-objective evolutionary approach to concurrently learn rule and data bases of linguistic fuzzy rule-based systems," IEEE Transactions on Fuzzy Systems, vol. 17, no. 5, pp. 1106-1122, 2009.
17. M. Antonelli, P. Ducange, B. Li, and F. Marcelloni, "Exploiting a new interpretability index in the multi-objective evolutionary learning of Mamdani fuzzy rule-based systems," in ISDA09. Pisa, Italy: IEEE, 2009, pp. 115-120.
18. D. D. Nauck, "Measuring interpretability in rule-based classification systems," in FUZZ-IEEE 2003, vol. 1, St. Louis, Missouri, USA, May, 25-28, 2003, pp. 196-201.
19. C. Mencar, G. Castellano, and A. M. Fanelli, "Distinguishability quantification of fuzzy sets," Information Sciences, vol. 177, no. 1, pp. 130-149, 2007.
20. P. Fazendeiro, J. V. de Oliveira, and W. Pedrycz, "A multiobjective design of a patient and anaesthetist-friendly neuromuscular blockade controller," IEEE Transactions on Biomedical Engineering, vol. 54, no. 9, pp. 1667-1678, 2007.
21. A. Botta, B. Lazzerini, F. Marcelloni, and D. C. Stefanescu, "Context adaptation of fuzzy systems through a multi-objective evolutionary approach based on a novel interpretability index," Soft Computing, vol. 13, no. 5, pp. 437-449, 2009.
22. R. Cannone, C. Castiello, C. Mencar, and A. M. Fanelli, "A study on interpretability conditions for fuzzy rule-based classifiers," in ISDA09. Pisa, Italy: IEEE, 2009, pp. 438-443.
23. J. M. Alonso, L. Magdalena, and G. González-Rodríguez, "Looking for a good fuzzy system interpretability index: An experimental approach," International Journal of Approximate Reasoning, vol. 51, pp. 115-134, 2009.
24. M. J. Gacto, R. Alcalá, and F. Herrera, "Integration of an index to preserve the semantic interpretability in the multi-objective evolutionary rule selection and tuning of linguistic fuzzy systems," IEEE Transactions on Fuzzy Systems, In press, 2009.
25. J. M. Alonso and L. Magdalena, "A conceptual framework for understanding a fuzzy system," in Joint IFSA-EUSFLAT, 2009, pp. 119-124.
26. J. M. Alonso, S. Guillaume, and L. Magdalena, "A hierarchical fuzzy system for assessing interpretability of linguistic knowledge bases in classification problems," in IPMU06, Paris, France, 2006, pp. 348-355.
27. T. L. Saaty, "A scaling method for priorities in hierarchical structures," Journal of Mathematical Psychology, vol. 15, pp. 234-281, 1977.
28. F. Zahedi, "The analytic hierarchy process: A survey of the method and its applications," Interfaces, vol. 16, no. 4, pp. 96-108, 1986.
29. T. L. Saaty, Multicriteria Decision Making: The Analytic Hierarchy Process. Revised and published by the author (original version published in 1980), McGraw-Hill, New York, 1988.
30. -, "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, vol. 48, pp. 9-26, 1990.
31. R. R. Yager, "On ordered weighted averaging aggregation operators in multicriteria decision-making," IEEE Transactions on Systems, Man and Cybernetics, vol. 18, pp. 183-190, 1988.
32. -, "Centered OWA operators," Soft Computing, vol. 11, pp. 631-639, 2007.
33. -, "Induced aggregation operators," Fuzzy Sets and Systems, vol. 137, pp. 59-69, 2003.
34. P. N. Smith, "Alternative forms of aggregation in the analytic hierarchy process: Ordered weighted averaging operators," Journal of Environmental Systems, vol. 31, no. 1, pp. 49-68, 2004.
35. Z. S. Xu and Q. L. Da, "The uncertain OWA operator," International Journal of Intelligent Systems, vol. 17, pp. 569-575, 2002.
36. R. R. Yager and A. Kelman, "An extension of the analythical hierarchy process using OWA operators," Journal of Intelligent and Fuzzy Systems, vol. 7, pp. 401-417, 1999.
37. R. R. Yager and J. Kacprzyk, The ordered weighted averaging operators: Theory and applications. Kluwer Academic Publishers, 1997.
38. L. A. Zadeh, "A computational approach to fuzzy quantifiers in natural languages," Computers and Mathematics with Applications, vol. 9, pp. 149-184, 1983.
39. G. A. Miller, "The magical number seven, plus or minus two: Some limits on our capacity for processing information," The Psychological Review, vol. 63, no. 2, pp. 81-97, 1956.
40. T. L. Saaty and M. S. Ozdemir, "Why the magic number seven plus or minus two," Mathematical and Computer Modelling, vol. 38, no. 3, pp. 233-244, 2003.
41. V. M. R. Tummala and H. Ling, "A note on the computation of the mean random consistency index of the analytic hierarchy process (AHP)," Theory and Decision, vol. 44, no. 3, pp. 221-230, 1998.