Abstract
Nowadays, Linguistic Modeling is considered as one of the most important applications of Fuzzy Set Theory, along with Fuzzy Control. Linguistic models have the advantage of providing a human-readable description of the system modeled in the form of a set of linguistic rules. In this contribution, we will analyze several approaches to improve the accuracy of linguistic models while maintaining their descriptive power. All these approaches will share the common idea of improving the way in which the Fuzzy Rule-Based System performs interpolative reasoning by improving the cooperation between the rules in the linguistic model Knowledge Base.
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Cordón, O., Herrera, F., del Jesus, M.J., Villar, P., Zwir, I. (2000). Different Proposals to Improve the Accuracy of Fuzzy Linguistic Modeling. In: Ruan, D., Kerre, E.E. (eds) Fuzzy If-Then Rules in Computational Intelligence. The Springer International Series in Engineering and Computer Science, vol 553. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4513-2_9
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DOI: https://doi.org/10.1007/978-1-4615-4513-2_9
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