Abstract
We present here a method that uses similarity relations to restore consistency in fuzzy gradual rules systems: we propose to transform potentially inconsistent rules by making their consequents more imprecise. Using a suitable similarity relation we obtain consistent rules with a minimum of extra imprecision. We also present an application to illustrate the approach.
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Drummond, I., Godo, L., Sandri, S. (2002). Restoring Consistency in Systems of Fuzzy Gradual Rules Using Similarity Relations. In: Bittencourt, G., Ramalho, G.L. (eds) Advances in Artificial Intelligence. SBIA 2002. Lecture Notes in Computer Science(), vol 2507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36127-8_37
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DOI: https://doi.org/10.1007/3-540-36127-8_37
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