Clustering is one of the data mining methods that partition large-sized data into subgroups
according to their similarities. K-means clustering algorithm works well in spherical or …

Improving carbon emission efficiency (CEE) is crucial to reducing CO 2 emissions. Most
studies on CO 2 emission are conducted at national and industrial scales, and city-scale …

Density peaks clustering (DPC) has been proved to be an effective clustering method and
applied to many scientific fields. It can detect the density peak within each cluster and assign …

The k-means, one of the most widely used clustering algorithm, is not only faster in
computation but also produces comparatively better clusters. However, it has two major …

Abstract The vessel Automatic Identification System (AIS) data collected by satellites have
the features of large coverage area and large data volume, and they are instantaneous …

In actual industrial production, the deterministic optimisation of the steam power system
cannot meet most production scenarios due to the influence of uncertain factors such as …

Clustering analysis is essential for obtaining valuable information from a predetermined
dataset. However, traditional clustering methods suffer from falling into local optima and an …

Based on China's provincial panel data from 2007 to 2017, this paper constructs a
comprehensive indicator system for high-quality development of manufacturing from eight …

Investigating crimes in selected areas, studying their occurrence and appropriate graphical
visualization may be an important supportive information for police units. Nowadays, the …

The advent of modern Internet of Things (IoT) architectures has led to ease in data collection
and availability. The data generated from such architectures are of large volume and …