Density peak clustering (DPC) algorithm has become a well-known clustering method
during the last decade, The research communities believe that DPC is a powerful tool …

Density peaks clustering (DPC) algorithm is a new algorithm based on density clustering
analysis, which can quickly obtain the cluster centers by drawing the decision diagram by …

As a recent swarm intelligence optimization algorithm, sparrow search algorithm (SSA) is
widely adopted in many real-world problems. However, the solutions to the limitations of …

With the rapid development of information technology, massive amount of data is generated.
How to discover useful information to support decision-making has become one of the …

The introduction of domain knowledge opens new horizons to fuzzy clustering. Then
knowledge-driven and data-driven fuzzy clustering methods come into being. To address …

DPC (Clustering by fast search and find of Density Peaks) algorithm and its variations
typically employ Euclidean distance, overlooking the diverse contributions of individual …

Density peak (DP) and density-based spatial clustering of applications with noise (DBSCAN)
are the representative clustering algorithms on the basis of density in unsupervised learning …

Indoor point cloud includes wall, ceiling, floor and many other indoor objects. Extraction of
wall, ceiling, floor and many objects in the room is the key for many applications including …

The widely applied density peak clustering (DPC) algorithm makes an intuitive cluster
formation assumption that cluster centers are often surrounded by data points with lower …

In density based clustering, the density peak algorithm has attracted much attention due to
its effectiveness and simplicity, and a vast amount of clustering approaches have been …