Abstract
It has been developed a C++ program that generates random fuzzy relations of a given dimension and computes their T-transitive closure (that contains the initial relation) and the new T-transitivized relation (that is contained in the initial relation) for the t-norms minimum, product and Lukasiewicz. It has been computed several distances between both transitive closure and transitivized relation with the initial relation one hundred times for each dimension and for each t-norm, and the results show that the average distance of the random fuzzy relations with the transitive closure is higher than the average distance with the new transitivized relation.
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Garmendia, L., Salvador, A. (2004). Comparing Transitive Closure with a New T-transitivization Method. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2004. Lecture Notes in Computer Science(), vol 3131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27774-3_29
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DOI: https://doi.org/10.1007/978-3-540-27774-3_29
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