Some New Algorithms of Clustering and Knowledge Reduced
Z.Pawlaks rough set theory is a new mathematical approach to uncertain and vague analysis. It is, no doubt, one of the most challenging areas, beside L.A.Zadehs fuzzy set theory, of modern computer applications nowadays and a new, very important and rapidly growing area of research and applications. In the paper, some different techniques and algorithms of clustering analysis and knowledge reduced are given base on Z.Pawlaks rough set theory. By the techniques of graph, lattice and matrix, we unify and generalize some Z.Pawlaks results. Moreover, our algorithms are numerical and carried out by the characteristic polyno- mial, which will be applied in data mining.
Ban Guining Zhang Xinzheng
College of Mathematics and Information Science Guangxi University Nanning, P.R.China, 530004 Faculty of Automation Guangdong University of Technology Guangzhou, P.R.China, 510090
国际会议
青岛
英文
2006-07-21（万方平台首次上网日期，不代表论文的发表时间）