Abstract
Fuzzy interpolative reasoning techniques can reduce the complexity of a sparse fuzzy rule-based system. In this paper, we present a new fuzzy interpola tive reasoning method via cutting and transformations techniques for sparse fuzzy rule-based systems. It produces more reasonable reasoning consequences than the ones presented in [1] and [3]. The proposed method provides a useful way to deal with fuzzy interpolative reasoning in sparse fuzzy rule-based systems.
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Ko, YK., Chen, SM. (2007). Fuzzy Interpolative Reasoning Via Cutting and Transformations Techniques. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_24
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DOI: https://doi.org/10.1007/978-3-540-73325-6_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
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