Abstract
In this work, the Interval Type-2 Fuzzy C-Mean (IT2FCM) algorithm was used for the design of Type-2 Fuzzy Inference Systems using centroids and fuzzy membership matrices for the lower and upper bound of the interval obtained by the IT2FCM algorithm in each data clustering realized by this algorithm, 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. (2014). Designing Type-2 Fuzzy Systems Using the Interval Type-2 Fuzzy C-Means Algorithm. In: Castillo, O., Melin, P., Pedrycz, W., Kacprzyk, J. (eds) Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Studies in Computational Intelligence, vol 547. Springer, Cham. https://doi.org/10.1007/978-3-319-05170-3_3
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