Application of the novel harmony search optimization algorithm for DBSCAN clustering

作者：

Highlights：

• Propose the K-DBSCAN clustering method, which can get K clusters of arbitrary shapes.

• The novel harmony search is presented to optimize the clustering parameters.

• Apply the novel harmony search to DBSCAN to realize the K-DBSCAN clustering.

摘要

•Propose the K-DBSCAN clustering method, which can get K clusters of arbitrary shapes.•The novel harmony search is presented to optimize the clustering parameters.•Apply the novel harmony search to DBSCAN to realize the K-DBSCAN clustering.

论文关键词：Clustering,DBSCAN,K-DBSCAN,Novel harmony search

论文评审过程：Received 19 September 2020, Revised 13 April 2021, Accepted 14 April 2021, Available online 20 April 2021, Version of Record 28 April 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115054