The task of finding natural groupings within a dataset exploiting proximity of samples is
known as clustering, an unsupervised learning approach. Density-based clustering …

Classifying the type of truck stops is vital in transportation planning and goods movement
strategies. Truck stops could be classified into primary or secondary. While the latter entail …

Mining of Spatial databases has been a subject of interest and a topic of research in recent
times. Social Media are the vast sources of geo-tagged information. This massive database …

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used
algorithm for exploratory clustering applications. Despite the DBSCAN algorithm being …

Technology innovation has provided the opportunity to study the characteristics of natural
human mobility. In this paper, we look at how to identify interesting clusters (by different …

Many density-based clustering algorithms already proposed in the literature are capable of
finding clusters with different shapes, sizes, and densities. Also, the noise points are …

The development of the artificial intelligence (AI) landscape has been impressive in virtually
all economic sectors in recent years. Our study discusses the over-concentration of AI …

Density-based clustering techniques are widely used in data mining on various fields.
DBSCAN is one of the most popular density-based clustering algorithms, characterized by …

Air pollution has a significant impact on environment resulting in consequences such as
global warming and acid rain. Toxic emissions from vehicles are one of the primary sources …

Cluster analysis or Clustering is considered a very important technique in the field of Data
Mining. There are many approaches to clustering ie, partitioning-based, hierarchal based …