Stability in Aggregation Operators

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dc.book.titleAdvances in Computational Intelligence
dc.contributor.authorGómez González, Daniel
dc.contributor.authorMontero De Juan, Francisco Javier
dc.contributor.authorRodríguez González, Juan Tinguaro
dc.contributor.authorRojas Patuelli, Karina
dc.contributor.editorGreco, Salvatore
dc.contributor.editorBouchon-Meunier, Bernadette
dc.contributor.editorFedrizzi, Mario
dc.contributor.editorMatarazzo, Benedetto
dc.contributor.editorYager, Ronald R.
dc.date.accessioned2023-06-20T05:46:28Z
dc.date.available2023-06-20T05:46:28Z
dc.date.issued2012
dc.description14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, Catania, Italy, July 9-13, 2012, Proceedings, Part III
dc.description.abstractAggregation functions have been widely studied in literature. Nevertheless, few efforts have been dedicated to analyze those properties related with the family of operators in a global way. In this work, we analyze the stability in a family of aggregation operators The stability property for a family of aggregation operators tries to force a family to have a stable/continuous definition in the sense that the aggregation of n − 1 items should be similar to the aggregation of n items if the last item is the aggregation of the previous n − 1 items. Following this idea some definitions and results are givenen
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/28628
dc.identifier.citationGómez, D., Montero, J., Rodríguez, J.T., Rojas, K.: Stability in Aggregation Operators. En: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., y Yager, R.R. (eds.) Advances in Computational Intelligence. pp. 317-325. Springer Berlin Heidelberg, Berlin, Heidelberg (2012)
dc.identifier.doi10.1007/978-3-642-31718-7_33
dc.identifier.isbn978-3-642-31717-0
dc.identifier.officialurlhttps//doi.org/10.1007/978-3-642-31718-7_33
dc.identifier.relatedurlhttp://link.springer.com/chapter/10.1007%2F978-3-642-31718-7_33
dc.identifier.urihttps://hdl.handle.net/20.500.14352/45538
dc.issue.number299
dc.language.isoeng
dc.page.final325
dc.page.initial317
dc.page.total626
dc.publication.placeBerlin
dc.publisherSpringer
dc.relation.ispartofseriesCommunications in Computer and Information Science
dc.relation.projectIDTIN2009-07901
dc.rights.accessRightsrestricted access
dc.subject.cdu519.22
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleStability in Aggregation Operatorsen
dc.typebook part
dc.volume.numberIII
dcterms.references1. Amo, A., Montero, J., Molina, E.: Representation of consistent recursive rules. European Journal of Operational Research 130, 29–53 (2001) 2. Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions, a Guide to Practitioners. Springer, Berlin (2007) 3. Calvo, T., Kolesarova, A., Komornikova, M., Mesiar, R.: Aggregation operators, properties, classes and construction methods. In: Calvo, T., et al. (eds.) Aggregation Operators New trends ans Aplications, pp. 3–104. Physica-Verlag,Heidelberg (2002) 4. Calvo, T., Mayor, G., Torrens, J., Suer, J., Mas, M., Carbonell, M.: Generation of weighting triangles associated with aggregation fuctions. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 8(4),417–451 (2000) 5. Cutello, V., Montero, J.: Hierarchical aggregation of OWA operators: basic measures and related computational problems. Uncertainty, Fuzzinesss and Knowledge-Based Systems 3, 17–26 (1995) 6. Cutello, V., Montero, J.: Recursive families of OWA operators. In: Proceedings FUZZ-IEEE Conference, pp. 1137–1141. IEEE Press, Piscataway (1994) 7. Cutello, V., Montero, J.: Recursive connective rules. International Journal of Intelligent Systems 14, 3–20 (1999) 8. Gomez, D., Montero, J.: A discussion of aggregation functions. Kybernetika 40, 107–120 (2004) 9. Gomez, D., Montero, J., Yañez, J., Poidomani, C.: A graph coloring algorithm approach for image segmentation. Omega 35, 173–183 (2007) 10. Gomez, D., Montero, J., Yañez, J.: A coloring algorithm for image classification. Information Sciences 176, 3645–3657 (2006) 11. Grabisch, M., Marichal, J., Mesiar, R., Pap, E.: Aggregation Functions. Encyclopedia of Mathematics and its Applications (2009) 12. Koles´arov´a, A.: Sequential aggregation. In: Gonz´alez, M., et al. (eds.) Proceedings of the Fifth International Summer School on Aggregation Operators, AGOP,pp. 183–187. Universitat de les Illes Balears, Palma de Mallorca (2009) 13. Montero, J., Gomez, D., Bustince, H.: On the relevance of some families of fuzzy sets. Fuzzy Sets and Systems 158, 2429–2442 (2007) 14. Montero, J., Lopez, V., Gomez, D.: The Role of Fuzziness in Decision Making. STUDFUZZ, vol. 215, pp. 337–349. Springer, Heidelberg (2007) 15. Rojas, K., Gomez, D., Rodrıguez, J.T., Montero, J.: Some Properties of Consistency in the Families of Aggregation Operators. In: Melo-Pinto, P., Couto, P., Serodio, C., Fodor, J., De Baets, B. (eds.) Eurofuse 2011. AISC, vol. 107, pp. 169–176. Springer, Heidelberg (2011) 16. Yager, R.R.: On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man and Cybernetics 18, 183–190 (1988) 17. Yager, R.R., Rybalov, A.: Nonconmutative self-identity aggregation. Fuzzy Sets and Systems 85, 73–82 (1997)
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