Abstract
Type-reduction is the key step of interval type-2 fuzzy c-means clustering(IT2FCM) algorithm, which determines the accuracy and efficiency of IT2FCM. In order to solve the problem of inefficiency of traditional IT2FCM algorithm which adopts iterative type-reduction method, an adaptive type-reduction(A-TR) method based on the result feedback was proposed, which was used to optimize the interval type-2 fuzzy clustering algorithm. The proposed A-TR method can find equivalent type-1 fuzzy sets which can instead of corresponding interval type-2 fuzzy sets according to the clustering results, so as to achieve the purpose of rapid type-reduction and improve the efficiency of traditional IT2FCM algorithm. We conducted several experiments with remote sensing images. The experimental results show that the proposed method not only improves the efficiency of IT2FCM, but also ensures the clustering effect.
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