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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CITATION STYLE
Chen, S. M., Cheng, S. H., & Chen, Z. J. (2015). A new fuzzy interpolative reasoning method based on the ratio of fuzziness of rough-fuzzy sets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9011, pp. 551–561). Springer Verlag. https://doi.org/10.1007/978-3-319-15702-3_53
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