A Chameleon Algorithm Based on P Systems with Active Promoters and Inhibitors

The purpose of this paper is to propose a new clustering algorithm, which combines membrane computing with a modified chameleon algorithm. The new algorithm is called as P-chameleon algorithm, which can obtain the knearest graphs, complete the partition of graph, aggregate subgraphs through communication rules and rewriting rules with the help of active promoters and inhibitors. The whole process of P-chameleon algorithm is shown by a 10 points test data set, which indicates the feasibility of the algorithm. All the processes are conducted in membranes. Cluster results via the famous wine data set verify that the proposed P-chameleon algorithm can cluster data set more accurate and less time consuming. The influences of parameters to the algorithm are also illustrated. The Pchameleon algorithm provides an alternative for traditional computing.