A new dynamic clustering algorithm for interval grey number

In this paper, the grey dynamic clustering algorithm of interval grey number is proposed by the joint application of the basic idea of fuzzy equivalent clustering and the method of grey system theory. Firstly, the similarity coefficient formula of interval grey number is discussed, and then the clustering of interval grey number is realized by making use of transitive closure method. This algorithm combines the grey system theory and the fuzzy set theory, which expands the range of classical equivalent clustering algorithms from the legible number to the interval grey number. Therefore, it´s more versatile, and its effectiveness is testified by an example.