Jiang, ZhenniLiu, XiyuSun, Minghe2023-04-032023-04-032019-07-31Jiang, Z., Liu, X., & Sun, M. (2019). A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System. Mathematical Problems in Engineering, 2019, 1713801. doi:10.1155/2019/17138011563-5147https://doi.org/10.1155/2019/1713801https://hdl.handle.net/20.500.12588/1807This study proposes a novel method to calculate the density of the data points based on K-nearest neighbors and Shannon entropy. A variant of tissue-like P systems with active membranes is introduced to realize the clustering process. The new variant of tissue-like P systems can improve the efficiency of the algorithm and reduce the computation complexity. Finally, experimental results on synthetic and real-world datasets show that the new method is more effective than the other state-of-the-art clustering methods.en-USAttribution 3.0 United Stateshttp://creativecommons.org/licenses/by/3.0/us/Article