Abstract
In this paper, we propose a new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on the ratio of fuzziness of polygonal rough-fuzzy sets, where the values of the antecedent variables and the consequence variables in the fuzzy rules are represented by polygonal rough-fuzzy sets. The experimental results show that the proposed fuzzy interpolative reasoning method outperforms the existing method for fuzzy interpolative reasoning in sparse fuzzy rule-based systems.
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Chen, SM., Cheng, SH., Chen, ZJ. (2015). A New Fuzzy Interpolative Reasoning Method Based on the Ratio of Fuzziness of Rough-Fuzzy Sets. In: Nguyen, N., Trawiński, B., Kosala, R. (eds) Intelligent Information and Database Systems. ACIIDS 2015. Lecture Notes in Computer Science(), vol 9011. Springer, Cham. https://doi.org/10.1007/978-3-319-15702-3_53
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DOI: https://doi.org/10.1007/978-3-319-15702-3_53
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