Biography
Prof. Xinquan Chen
Prof. Xinquan Chen
Anhui Polytechnic University, China
Title: A shrinking synchronization clustering algorithm based on a linear weighted Vicsek model
Abstract: 
Clustering tries to find some distributions and patterns in unlabeled datasets. Synchronization clustering has become an important direction after the original Synchronization Clustering (SynC) algorithm was published in 2010. This paper presents a Shrinking Synchronization Clustering (SSynC) algorithm by using a linear weighted Vicsek model. SSynC algorithm is developed based on SynC algorithm and a more Effective Synchronization Clustering (ESynC) algorithm. After some analysis and comparison, we find that SSynC algorithm has better synchronization effect than SynC algorithm based on an extensive Kuramoto model and has similar synchronization effect with ESynC algorithm based on a linear version of Vicsek model. In the simulations, several clustering algorithms are used as comparative algorithms. By some simulated experiments of some artificial datasets, several real datasets and three picture datasets, we observe that SSynC algorithm not only gets better local synchronization effect but also needs less iterative times and time cost than SynC algorithm. Moreover, SSynC algorithm needs less time cost than ESynC algorithm and almost get the same local synchronization effect and the same iterative times. Extensive comparison experiments with some class clustering algorithms demonstrate the effectiveness of our algorithm.

Biography: 
Xinquan Chen is a professor and master supervisor of the School of Computer & Information, Anhui Polytechnic University, Wuhu, Anhui, PR China. He received the Ph.D degree from South China University of Technology in 2007 and the post-doctorate career from University of Electronic Science and Technology of China in 2016. He is a member of System Simulation & Simulation Technology Application Committee, Editorial Board Member of Journal of Anhui Polytechnic University, CCF Member. His research interests include data mining, machine learning, clustering algorithms, and optimization method.
At present, he has presided over the completion of 3 provincial-level scientific research projects and 3 university-level scientific research projects. As the first author, he has published more than 40 academic papers in SCI/EI source journals, CSCD journals and EI conferences. Among them, there are 5 journal articles from CCF recommends international SCI, 11 papers indexed by EI and 8 papers indexed by CSCD. He is a reviewer of multiple international SCI journals.