|Table of Contents|

Attribute reduction algorithm based on rough set in incomplete interval-valued information system


Research Field:
Publishing date:


Attribute reduction algorithm based on rough set in incomplete interval-valued information system
Zeng LingHe PuyanFu Min
School of Mathematics and Computing Science,Guilin University of Electronic Technology,Guilin 541004,China
rough sets incomplete interval-valued information system tolerance relation based on similarity connection degree two-parameter assignment reduction
This paper discusses the attribute reduction in incomplete interval-valued information system.A tolerance relation based on similarity connection degree is defined and the extension of a rough set model based on this relation is proposed.By defining the two-parameter assignment reduction and identical-discrepancy-contrary discernibility matrix,a two-parameter assignment reduction algorithm based on the identical-discrepancy-contrary discernibility matrix is proposed.According to the requirements of different users and the distribution characteristics of the data set,the parameters can be dynamically adjusted to be more realistic.A numerical example is given and the effect of different parameters for reduction is investigated.


[1] Durairaj M,Meena K.A hybrid prediction system using rough sets and artificial neural networks[J].International Journal of Innovative Technology and Creative Engineering,2011,1(7):16-23.
[2]Lutfi O M,Aris I,Abdullah S M,et al.Knowledge discovery in distance relay event report:A comparative data-mining strategy of rough set theory with decision tree[J].Power Delivery,2010,25(4):2264-2287.
[3]Krysckiewicz M.Rough set approach to incomplete information system[J].Information Sciences,1988,112:39-49.
[4]Stefamowski J,Tsoukeas A.On the extension of rough sets under incomplete information[J].International Journal of Intelligent System,1999,16(1):29-38.
Wang Guoyin.Extension of Rough set under incomplete information systems[J].Journal of Computer Research and Development,2002,39(10):1238-1243.
Huang Bing,Zhou Xianzhong.Extension of rough set model based on connection degree under incomplete information systems[J].Systems Engineering—Theory and Practice,2004,24(1):88-92.
[7]Yang Xibei,Yu Dongjun,Yang Jingyu,et al.Dominance-based rough set approach to incomplete interval-valued information system[J].Data and Knowledge Engineering,2009(68):1331-1347.
Wei Lihua,Tang Zhenmin,Yang Xibei,et al.Rough set theory in incomplete interval-valued information system[J].Information and Control,2009,38(1):286-292.
Chen Zichun,Qin Keyun.Attribute reduction of interval-valued information system based on variable precision tolerance relation[J].Computer Science,2009,36(3):163-166.
Huang Hengqiu,Zeng Ling.Rough classification method in incomplete decision information system with hybrid value[J].Computer Engineering and Applications,2011,47(28):48-51.
[11]Dai Liuling,Huang Bing,Yang Dongxiao.A connection degree-based rough sets model and its application to knowledge reduction[A].Eighth ACIS International Conference on Software Engineering,Artificial Intelligence,Networking,and Parallel/Distributed Computing[C].Qingdao,China:IEEE Press,2007:1017-1021.
[13]Yang Ping,Li Jisheng,Huang Yongxuan.An attribute reduction algorithm by rough set based on binary discernibility matrix[A].Fifth International Conference on Fuzzy Systems and Knowledge Discovery[C].Jinan,China:IEEE Press,2008:276-280.
Zhang Nan,Miao Duoqian,Yue Xiaodong.Approaches to knowledge reduction in interval-valued information systems[J].Journal of Computer Research and Development,2010,47(8):1362-1371.


Last Update: 2013-08-31