Clustering is an important data analysis technique. However, due to the diversity of datasets,
each clustering algorithm is unable to produce satisfactory results on some particular …

Innovative Industrial Clusters (IIC), characterized by geographical aggregation and
technological collaboration among technology enterprises and institutions, serve as pivotal …

Identifying black spots effectively and accurately is a pivotal and challenging task to improve
road traffic safety. A novel black spot identification model is proposed by integrating the GIS …

Despite the significant impacts of biomass burning (BB) on global climate change and
regional air pollution, there is a relative lack of research on the temporal trends and …

Cross-manifold clustering is an extreme challenge learning problem. Since the low-density
hypothesis is not satisfied in cross-manifold problems, many traditional clustering methods …

Several popular density-based methods for unsuper-vised and semi-supervised learning
tasks, including clustering and classification, can be formulated as instances of a framework …

Identifying clusters of arbitrary shapes and constantly processing the newly arrived data
points are two critical challenges in the study of clustering. This paper proposes a dynamic …