Work place: Institute of Disaster Prevention Science and Technology. Sanhe, Hebei. China
Research Interests: Artificial Intelligence, Data Mining, Data Structures and Algorithms, Artificial intelligent in learning
Professor Li Zhong was born in Zhu-cheng city, Shan dong province of China. He obtained his Ph.D. degree in Earth Information Science from China University of Mine and Technology (Beijing) at 2007. His first degree is Bachelor of Science in Basic Mathematics from Shandong University at 1987 and master degree is Master of Industry in Mechanics from Dalian University of Technology at 1990. He works in Dean of Information Engineering and Computer Science, Institute of Disaster Prevention of China, from 2008. Prior to joining Institute of Disaster Prevention of China, Prof. Li is a associate professor in Weifang University, Engineer in Huaguang Company. In 2002, he was a visiting scholar in the e-government research in State Information Center of China. His specialties include, but not limited to, data mining, Artificial Intelligence, 3S technology. Prof. Li Zhong is a fellow of China Computer Federation and a member of Intelligent Computing Council of Operations Research Society of China.
DOI: https://doi.org/10.5815/ijeme.2011.01.03, Pub. Date: 29 Jul. 2011
This paper makes analysis on theories of D-S evidential reasoning, rough sets and extenics sets, the three of which hold similarities in defining uncertainty sets. It’s feasible to introduce relevant theories and methods of extenics into information fusion and a method of extenics fusion (MEF) is presented as well. The method combines extenic correlation function with Dempster method and is considered to be a good solution in solving evidence collision and BPA function in information fusion method basing on D-S evidential reasoning. With the difference of transfer functions, the paper designs a method of extenics fusion. The simulation test results show that MEF is better than the traditional D-S evidential reasoning and is applicable to all kinds of evaluation problems.[...] Read more.
DOI: https://doi.org/10.5815/ijmecs.2011.02.05, Pub. Date: 8 Apr. 2011
This paper makes analysis on theories of D-S evidential reasoning, rough sets, and extenic sets; and indicates that there are some similarities among the three theories in defining uncertainty sets. Therefore, it’s feasible to introduce relevant theories and methods of extenics into information fusion and a method of extenics fusion (MEF) is presented as well. The method combines extenic correlation function with Dempster rule and is considered a good solution for problems of evidence collision and BPA function in information fusion method based on D-S evidential reasoning. The simulation test shows that MEF is better than the traditional D-S evidential reasoning and is applicable to assess all kinds of problems. Using the method of this paper to evaluate surface water in one area of Northern China, the results were consistent with the fact.[...] Read more.
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