Aggregating fuzzy implications to measure group consensus

Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013

Volumn , Issue , 2013, Pages 1016-1021

  Beliakov, Gleb ^a   James, Simon ^a   Calvo, Tomasa ^b  

^a DEAKIN UNIVERSITY   (Australia)

^b UNIVERSITY OF ALCALÁ   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

COMPONENTWISE; FUZZY IMPLICATIONS; GROUP CONSENSUS; INTERPRETABILITY;

FUZZY LOGIC;

EID: 84886562929     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IFSA-NAFIPS.2013.6608539     Document Type: Conference Paper

References (20)

1. M. Baczýnski and J. Balasubramaniam. Fuzzy Implications. Springer, Berlin, Heidelberg, 2008.
2. M. Baczýnski and J. Drewniak. Monotonic fuzzy implications. In Fuzzy Systems in Medicine, pages 90-111. Springer, Berlin, Heidelberg, 2000.
3. G. Beliakov, S. James, J. Mordelov́a, T. R̈uckschlossov́ a, and R. R. Yager. Generalized Bonferroni mean operators in multi-criteria aggregation. Fuzzy Sets and Systems, 161:2227-2242, 2010.
4. G. Beliakov, A. Pradera, and T. Calvo. Aggregation Functions: A Guide for Practitioners. Springer, Heidelberg, 2007.
5. C. Bonferroni. Sulle medie multiple di potenze. Bollettino Matematica Italiana, 5:267-270, 1950.
6. H. Bustince, E. Barrenechea, and M. Pagola. Restricted equivalence functions. Fuzzy Sets and Systems, 157:2333-2346, 2006.
7. F. J. Cabrerizo, S. Alonso, I. J. Ṕerez, and E. Herrera-Viedma. On consensus measures in fuzzy group decision making. In Proceedings of MDAI 2008, pages 86-97. 2008.
8. F. Chiclana, J. M. Tapia-Garćia, M. J. del Moral, and E Herrera- Viedma. A statistical comparative study of different similarity measures of consensus in group decision making. Information Sciences, 221:110- 123, 2013.
9. A. Dvořŕak and M. Hoľcapek. Fuzzy measures and integrals defined on algebras of fuzzy subsets over complete residuated lattices. Information Sciences, 185:205-229, 2012.
10. J. L. Garćia-Lapresta and D. P. Roḿan. Some measures of consensus generated by distances on weak orders. In Proceedings of XIV Congreso Espãnol sobre Tecnoloǵias y Ĺogica fuzzy, pages 477-483. Cuencas Mineras, 17 -19 September, 2008.
11. M. Grabisch, J.-L. Marichal, R. Mesiar, and E. Pap. Aggregation Functions. Cambridge University press, Cambridge, 2009.
12. J. Mart́in and G. Mayor. Multi-argument distances. Fuzzy Sets and Systems, 167:92-100, 2011.
13. M. Mas, M. Monserrat, J. Torrens, and E. Trillas. A survey on fuzzy implication functions. IEEE Transactions on Fuzzy Systems, 15(6):1107- 1121, 2007.
14. J. Mordelov́a and T. R̈uckschlossov́a. ABC-aggregation functions. In Proc. of the 5th Intl. Summer School on Aggregation Operators, Palma de Mallorca, Spain, 2009.
15. E. Szmidt and J. Kacprzyk. Analysis of consensus under intuitionistic fuzzy preferences. In Proc. Int. Conf. in Fuzzy Logic and Technology, pages 79-82. De Montfort University, Leicester, UK, 2001.
16. J. M. Tastle and W. J. Tastle. Extending the consensus measure: analyzing ordinal data with respect to extrema. In Proc. of ISECON 2005, v22, pages 1-5, Columbus OH, USA, 2005.
17. W. J. Tastle, M. J. Wierman, and U. R. Dumdum. Ranking ordinal scales using the consensus measure. Issues in Information Systems, 185:96- 102, 6.
18. Y. Torra, V. Narukawa. Modeling Decisions. Information Fusion and Aggregation Operators. Springer, Berlin, Heidelberg, 2007.
19. R. R. Yager. On generalized Bonferroni mean operators for multi-criteria aggregation. International Journal of Approximate Reasoning, 50:1279- 1286, 2009.
20. R. R. Yager, G. Beliakov, and S. James. On generalized Bonferroni means. In Proc. Eurofuse 2009 Conference, Pamplona, Spain, 2009.