Fuzzy Clustering with Uninorm‐Based Distance Measure

In the paper we suggest an algorithm of fuzzy clustering with uninorm-based distance measure. The algorithm follows a general scheme of fuzzy c-means (FCM) clustering, but in contrast to the existing algorithm it implements logical distance between data instances. The centers of the clusters calculated by the algorithm are less deviated and are concentrated in the areas of the actual centers of the clusters that results in more accurate recognition of the number of clusters and of data structure.