Abstract
An efficient centroid type-reduction strategy for general type-2 fuzzy set is proposed by Liu. In Liu’s method, a type-2 fuzzy set will be decomposed into several interval type-2 fuzzy sets. However, if the membership function of the type-2 fuzzy set is concave, the primary membership of these interval type-2 fuzzy sets on some points may not have only one continuous interval. Existing type-reduction algorithms, such as Karnik-Mendel algorithm and Enhanced Karnik-Mendel algorithm, can not deal with this problem. We propose a method to decompose this problem into several subproblems which can then be solved by existing type-reduction algorithms. The union of the solutions to the subproblems is the final solution to the original problem.
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Xie, BK., Lee, SJ. (2015). Type-Reduction for Concave Type-2 Fuzzy Sets. In: Barbucha, D., Nguyen, N., Batubara, J. (eds) New Trends in Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 598. Springer, Cham. https://doi.org/10.1007/978-3-319-16211-9_9
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DOI: https://doi.org/10.1007/978-3-319-16211-9_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16210-2
Online ISBN: 978-3-319-16211-9
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