Abstract
In this work, the Interval Type-2 Fuzzy C-Means (IT2FCM) algorithm is used for the design of Interval Type-2 Fuzzy Inference Systems using the centroids and fuzzy membership matrices for the lower and upper bound of the intervals obtained by the IT2FCM algorithm in each data clustering realized by this algorithm, and with these elements obtained by IT2FCM algorithm we design the Mamdani, and Sugeno Fuzzy Inference systems for classification of data sets and time series prediction.
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Rubio, E., Castillo, O., Melin, P. (2016). Interval Type-2 Fuzzy System Design Based on the Interval Type-2 Fuzzy C-Means Algorithm. In: Collan, M., Fedrizzi, M., Kacprzyk, J. (eds) Fuzzy Technology. Studies in Fuzziness and Soft Computing, vol 335. Springer, Cham. https://doi.org/10.1007/978-3-319-26986-3_8
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DOI: https://doi.org/10.1007/978-3-319-26986-3_8
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