Fuzzy Temporal Constraints Based Fuzzy Clustering Algorithm for Temporal Dadaset

Fuzzy c-means plays an important role in investigating the structure of dataset. In order to clustering the temporal or spatial dataset, constraints-equipped version of fuzzy c-means was proposed in literature. This paper focuses on the clustering of temporal dataset, and presents a new version of constraints-equipped fuzzy c-means algorithm, where the temporal constraints are described by fuzzy sets rather than crisp intervals. This new version fuzzy c-means overcomes the disadvantages of the old version where strict requirements on the choosing of the parameters are needed and in many cases the result is not so satisfactory. The experiments carried in this paper illustrate the good performance of the new version of temporal constraints-equipped fuzzy c-means.