Characterizing Quantifier Fuzzification Mechanisms: a behavioral guide for practical applications
May 11, 2016 Β· Declared Dead Β· π Fuzzy Sets Syst.
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Authors
F. Diaz-Hermida, M. Pereira-FariΓ±a, Juan C. Vidal, A. Ramos-Soto
arXiv ID
1605.03506
Category
cs.AI: Artificial Intelligence
Citations
13
Venue
Fuzzy Sets Syst.
Last Checked
4 months ago
Abstract
Important advances have been made in the fuzzy quantification field. Nevertheless, some problems remain when we face the decision of selecting the most convenient model for a specific application. In the literature, several desirable adequacy properties have been proposed, but theoretical limits impede quantification models from simultaneously fulfilling every adequacy property that has been defined. Besides, the complexity of model definitions and adequacy properties makes very difficult for real users to understand the particularities of the different models that have been presented. In this work we will present several criteria conceived to help in the process of selecting the most adequate Quantifier Fuzzification Mechanisms for specific practical applications. In addition, some of the best known well-behaved models will be compared against this list of criteria. Based on this analysis, some guidance to choose fuzzy quantification models for practical applications will be provided.
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