N-dimensional views in fuzzy data analysis

This paper considers the problem of detecting local substructures of a system in a high dimensional data space by applying the fuzzy clustering technique. First, a new objective function to improve existing approaches is proposed, and then an efficient algorithm for detecting clusters with different dimensionalities is presented. Finally, a new type of fuzzy modeling using elliptic membership functions is discussed.