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Titlebook: Eurofuse 2011; Workshop on Fuzzy Me Pedro Melo-Pinto,Pedro Couto,Bernard Baets Conference proceedings 2012 Springer Berlin Heidelberg 2012

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https://doi.org/10.1007/978-3-322-98797-6s. Smooth t-norms and t-conorms, nullnorms and some kinds of uninorms, copulas and quasi-copulas have been characterized in this context. In this paper discrete aggregation functions with the kernel property (which implies the smoothness property) are investigated. Some properties and characterizati
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On the Usefulness of Interval Valued Fuzzy Sets for Learning Fuzzy Rule Based Classification Systemse of these systems may be their lack of accuracy when dealing some complex systems, due to the inflexibility of the concept of linguistic variable, which imposes hard restrictions to the fuzzy rule structure. For example, sometimes when the classes are overlapped, we have not exact knowledge about t
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A Possibilistic Logic View of Sugeno Integralsnimum and the maximum of the input criteria values. They can model sophisticated aggregation schemes through a system of priorities that applies to any subset of criteria and can take into account some kind of synergy inside subsets of criteria. Although a given Sugeno integral specifies a particula
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Decomposition of Possibilistic Belief Functions into Simple Support Functionshis decomposition is unique. Recently, a qualitative counterpart to Shafer evidence theory has been proposed. The mass functions in Shafer (addition-based) evidence theory are replaced by basic possibilistic assignments. The sum of weights is no longer 1, but their maximum is equal to 1. In such a c
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