Xiao-Jun Zeng

Dr. Xiao-Jun Zeng

School of Computer Science, University of Manchester, Manchester, UK

Research Focus & Metrics

Academic Career Length

33Years (1994-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2011 in Journal of Computational Science
Verified
Journal Article
Closed access
JBJohan Bollen
Johan Bollen
HMHuina Mao
Huina Mao
Xiao-Jun ZengXiao-Jun Zeng
Xiao-Jun Zeng

11 January 2018 in Sustainability
Verified
Journal Article
Open access
PDF file
HLHuchang Liao
Huchang Liao
MTMing Tang
Ming Tang
LLLi Luo
Li Luo
CLChunyang Li
Chunyang Li
Francisco ChiclanaFrancisco Chiclana
Francisco Chiclana
Xiao-Jun ZengXiao-Jun Zeng
Xiao-Jun Zeng
With the rapid development of “Internet plus”, medical care has entered the era of big data. However, there is little research on medical big data (MBD) from the perspectives of bibliometrics and visualization. The substantive research on the basic aspects of MBD itself is also rare. This study aims to explore the current status of medical big data through visualization analysis on the journal papers related to MBD. We analyze a total of 988 references which were downloaded from the Science Citation Index Expanded and the Social Science Citation Index databases from Web of Science and the time span was defined as “all years”. The GraphPad Prism 5, VOSviewer and CiteSpace softwares are used for analysis. Many results concerning the annual trends, the top players in terms of journal and institute levels, the citations and H-index in terms of country level, the keywords distribution, the highly cited papers, the co-authorship status and the most influential journals and authors are presented in this paper. This study points out the development status and trends on MBD. It can help people in the medical profession to get comprehensive understanding on the state of the art of MBD. It also has reference values for the research and application of the MBD visualization methods.


1 March 2015 in Knowledge-Based Systems
Verified
Journal Article
Closed access
HLHuchang Liao
Huchang Liao
Zeshui XuZeshui Xu
Zeshui Xu
Xiao-Jun ZengXiao-Jun Zeng
Xiao-Jun Zeng
JMJose M. Merigo
Jose M. Merigo

1 May 1995 in IEEE Transactions on Fuzzy Systems
Verified
Journal Article
Closed access
Xiao-Jun ZengXiao-Jun Zeng
Xiao-Jun Zeng
MSM.G. Singh
M.G. Singh
In this paper, the approximation properties of MIMO fuzzy systems generated by the product inference are discussed. We first give an analysis of fuzzy basic functions (FBF's) and present several properties of FBF's. Based on these properties of FBF's, we obtain several basic approximation properties of fuzzy systems: 1) basic approximation property which reveals the basic approximation mechanism of fuzzy systems; 2) uniform approximation bounds which give the uniform approximation bounds between the desired (control or decision) functions and fuzzy systems; 3) uniform convergent property which shows that fuzzy systems with defined approximation accuracy can always be obtained by dividing the input space into finer fuzzy regions; and 4) universal approximation property which shows that fuzzy systems are universal approximators and extends some previous results on this aspect. The similarity between fuzzy systems and mathematical approximation is discussed and an idea to improve approximation accuracy is suggested based on uniform approximation bounds.

1 May 1994 in IEEE Transactions on Fuzzy Systems
Verified
Journal Article
Closed access
Xiao-Jun ZengXiao-Jun Zeng
Xiao-Jun Zeng
MSM.G. Singh
M.G. Singh