[1]李龙澍,程慧霞,卢冰原.基于凸Rough集的数据约简和规则发现研究[J].东南大学学报(自然科学版),2002,32(2):201-205.[doi:10.3969/j.issn.1001-0505.2002.02.012]
 Li Longshu,Cheng Huixia,Lu Bingyuan.Study on data reduction and rules discovery based on convex Rough set[J].Journal of Southeast University (Natural Science Edition),2002,32(2):201-205.[doi:10.3969/j.issn.1001-0505.2002.02.012]
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基于凸Rough集的数据约简和规则发现研究()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
32
期数:
2002年第2期
页码:
201-205
栏目:
自动化
出版日期:
2002-03-20

文章信息/Info

Title:
Study on data reduction and rules discovery based on convex Rough set
作者:
李龙澍 程慧霞 卢冰原
安徽大学计算智能与信号处理实验室,合肥 230039
Author(s):
Li Longshu Cheng Huixia Lu Bingyuan
Intelligence Computing and Signal Processing Laboratory, Anhui University, Hefei 230039, China
关键词:
数据约简 规则发现 Rough集 凸Rough集
Keywords:
data reduction rules discovery rough set convex rough set
分类号:
TP18
DOI:
10.3969/j.issn.1001-0505.2002.02.012
摘要:
为了有效地从凸序列中约简数据和发现知识,解决Rough集中的凸序列处理问题,在深入研究凸序列和Rough集理论的基础上,提出了凸Rough集模型,定义了凸Rough集和凸Rough模糊集,给出了凸Rough模糊集的隶属函数和应用凸Rough集进行数据约简及规则发现的算法.最后分析了一个应用案例,验证了模型的可行性,表明应用凸Rough集模型可以更好地进行数据约减和规则发现.
Abstract:
In order to reduce data, discover knowledge from convex serial, and to process convex serial in rough set, convex serial and rough set theory were studied thoroughly and a convex rough set model is presented. Convex rough set and convex rough fuzzy set are defined and the membership function of the convex rough fuzzy set is given. The algorithms of data reduction and rules discovery using convex rough set are also introduced. Finally, an application case is analyzed. The results show that the presented model can be applied conveniently to data reduction and rules discovery with computing better decision.

参考文献/References:

[1] Pawlak Z.Rough sets [J].International Journal of Computer and Information Sciences, 1982,11(5):341-356.
[2] Pawlak Z,Grzymala-busse J,Slowinski R,et al.Rough sets [J]. Communications of the ACM, 1995,38(11):89-95.
[3] Pawlak Z,Slowinski R.Rough set approach to multi-attribute decision analysis [M].ICS Research Report 36,Warsaw University of Technology,1993.1-17.
[4] Chmielewski M R,Grzymala-Busse J W.Global discretization of continuous attributes as preprocessing for machine learning [J]. International Journal of Approximate Reasoning,1996,15:319-331.
[5] Pawlak Z.Rough set:theoretical aspects of reasoning about data [M].Dordrecht Boston,Londom:Kluwer Academic Publishers,1991.68-162.
[6] Chan C C.A rough set approach to attribute generalization in data mining [J]. Journal of Information Sciences,1998,107:169-176.
[7] Lingras P J,Yao Y Y.Data mining using extensions of the rough set model [J].Journal of the American Society for Information Science,1998,49(5):415-422.
[8] Pawlak Z.Rough set approach to knowledge-based decision support [J]. European Journal of Operational Research,1997,99:48-57.
[9] 刘大有,杨鲲,唐海鹰,等.凸函数证据理论模型[J].计算机研究与发展,2000,37(2):175-181.
  Liu Dayou,Yang Kun,Tang Haiying,et al.A convex evidence theory model [J]. J of Computer Research and Development.2000,37(2):175-181.(in Chinese)
[10] 王珏,王任,苗夺谦,等.基于Rough Set理论的“数据浓缩”[J].计算机学报,1998,21(5):393-400.
  Wang Jue,Wang Ren,Miao Duoqian,et al.Data enriching based on rough set theory.[J] Chinese J Computers,1998,21(5):393-400.(in Chinese)
[11] 尹旭日,周志华,何佳洲,等.一种基于Rough集理论的数据过滤方法 [J].计算机研究与发展,2000,37(9):1082-1086.
  Yin Xuri,Zhou Zhihua,He Jiazhou,et al.An algorithm based on rough set theory for data filtering [J].J.of Computer Research and Development,2000,37(9):1082-1086.(in Chinese)
[12] Düntsch I,Gediga G.Uncertainty measures of rough set predication [J].Artificial Intelligence,1998,106(1):109-137.
[13] Yoon J P,Kerschberg L.A framework for knowledge discovery and evolution in databases [J]. IEEE Trans on Knowledge and Data Engineering,1993,5(6):973-979.
[14] Agrawal R,Imielinski T,Swami A.Database mining:A performance perspective.IEEE Trans on Knowledge and Data Engineering,1993,5(6):914-925.
[15] Li Longshu,Cheng Huixia,Zhu Yu.Research on data mining framework based on rough sets [A].In:Proc of International Symposium on Future Software Technology [C].Guiyang China.2000.326-328.

备注/Memo

备注/Memo:
基金项目: 国家“863”资助项目( 863-306-ZD05-01-8),教育部骨干教师资助项目(2000-65).
作者简介: 李龙澍(1956—),男,教授,LShLi@ahu.edu.cn.
更新日期/Last Update: 2002-03-20