New ways to calculate centers for interval data in fuzzy clustering algorithms

In this paper, we propose some new forms obtain centers of the groups given interval membership, where that membership is the pertinence of each object to the prototypes of all clusters using intervals distance valued (IMV). In this case, we will perform a comparative analysis using the three different approaches proposed in this paper, using seven interval-based datasets (four synthetic and three real datasets). As a result of this analysis, we will observe that the proposed approaches achieved better performance than all analyzed methods for interval-based methods.