Abstract
MST clustering algorithm can detect data clusters with irregular boundaries. For a weighted complete graph the feasible solutions to the MST problem is non-unique. Membrane computing known for its characteristics of distribution and maximal parallelism can properly reduce the complexity of processing a MST of a graph. This paper combines MST clustering algorithm and membrane computing by designing a specific P system. The designed P system realizes the process of an improved MST clustering by collecting all feasible solutions to the MST problem together preserving proper edges and deleting redundant heavy edges. The improved MST clustering method efficiently enhances the quality of clustering and proved to be feasible through an instance.
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