Social network analysis has important research significance in sociology, business analysis,
public security, and other fields. The traditional Louvain algorithm is a fast community …

To properly monitor dynamic large-scale processes, a new distributed dynamic process
monitoring strategy named multi-block dynamic weighted principal component regression …

This work focuses on the changing demands which is contributed to dynamism and
complexity of the routing problems. Most of vehicle routing problems (VRP) have been …

Intelligent manufacturing process needs to adopt distributed monitoring scenario due to its
massive, high-dimensional and complex data. Distributed process monitoring has been …

Graphs are considered to be one of the best studied data structures in discrete mathematics
and computer science. Hence, data mining on graphs has become quite popular in the past …

With the growing complexity of industrial processes, the scale of production processes tends
to be large. The significant amount of measurement data in large‐scale processes poses …

Computing the all pair shortest paths in a graph is a widely used solution, but a time-
consuming process too. The popularly used conventional algorithms rely solely on the …

In recent years, the real world complex network analysis has become an interesting
research area. Network consists of entities and links. Similar entities in a network falls into …

In social network analysis and graph theory, influence node is a measure that used to
quantify the importance of a node in that network. Community is a collection of node …

In this paper, we propose a scalable method for finding the evolving communities in complex
networks. The various network properties that are prominent in real-world networks are …