Abstract
In this paper, we present optimization of the Interval Type-2 Fuzzy Possibilistic C-Means (IT2FPCM) algorithm using Particle Swarm Optimization (PSO), with the goal of automatically finding the optimal number of clusters and the optimal lower and upper limit of Fuzzy and Possibility exponents of weight of the of the IT2FPCM algorithm, and also the centroids of clusters of each dataset tested with the IT2FPCM algorithm optimized using PSO.
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Rubio, E., Castillo, O. (2017). Interval Type-2 Fuzzy Possibilistic C-Means Optimization Using Particle Swarm Optimization. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_4
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