In the era of big data, unsupervised learning algorithms such as clustering are particularly
prominent. In recent years, there have been significant advancements in clustering algorithm …

With the increasing number of China's automobile production and ownership, the
automobile industry faces new opportunities as well as challenges. Automobile industry …

A dynamic clustering algorithm was proposed based on consistent matrix of dependent
function for time series multi-dimensional data. Further, improved standard dependent …

How to arrange sales staff to visit offline stores reasonably is a critical task in the Fast
Moving Consumer Goods (FMCG) industry. Based on the K-means and Dijkstra algorithms …

With the emergence of all kinds of location services applications, massive location data are
collected in real time. A hierarchical fast density clustering algorithm, DBSCAN (density …

According to the demand analyses of large machine tool parts cutting database system, the
parameters of main attributes and their mutual relationships were determined in the system …

Data clustering is the process of identifying natural groupings or clusters based on a certain
similarity measure in muti-dimensional data. Aiming at the dynamic clustering problem …

Logistics network includes regional logistics network and urban logistics network. In this
paper, the urban logistics network is taken as the research object. With the improvement of …

In modern systems, there is a tendency to model issues more accurately with low
computational cost and considering multiscale decision-making which increases the …