Optimization of the Interval Type-2 Fuzzy C-Means using Particle Swarm Optimization

This paper presents the implementation of Particle Swarm Optimization for the optimization of Interval Type-2 Fuzzy C-Means algorithm, this in order to automatically find the optimal number of clusters c and the interval of fuzzification or weight exponent [m1, m2], using as objective function for optimization algorithm an index cluster validation.

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