|Table of Contents|

Incomplete decision rule acquisition based on multigranulation theory


Research Field:
Publishing date:


Incomplete decision rule acquisition based on multigranulation theory
Wang Lijuan12Yang Xibei12Yang Jingyu1Wu Chen2
1.School of Computer Science and Engineering,NUST,Nanjing 210094,China; 2.Department of Computer Science and Engineering,Jiangsu University of Science and Technology, Zhenjiang 212003,China
multigranulation theoryincomplete decision systemapproximate distribution reductdecision rule acquisition
Multigranulation theory is introduced into the incomplete decision systems.According to the incompleteness,the similarity relationbased incomplete multigranulation rough set model is proposed combining with the nonsymmetric similarity relation,and its properties are discussed.The investigation focuses on the attribute reductions and decision rule acquisitions in the new model.Multigranulation theory and approximate distribution reduction are combined to solve the two problems,and the concept of the incomplete multigranulation approximate distribution reduction is presented.All the simplified certain decision rules and the simplified possible decision rules are obtained.A numerical example is employed to substantiate the conceptual arguments.The research results show that the methods of multigranulation approximate distribution reduct and rule acquisition are more reasonable and effective than the original methods in single granulation.


[1]Zadeh L A.Fuzzy logic=Computing with words[J].IEEE Transactions on Fuzzy Systems,1996,4(2):103-111.
[2]Thiele H.On semantic models for investigating computing with words[A].Proceedings of the Second International Conference on Knowledge Based Intelligent Electronic Systems[C].USA:IEEE,1998:32-98.
[3]Lin T Y.Granular computing on binary relations I:data mining and neighborhood systems[A].Rough Sets and Knowledge Discovery[C].Heidelberg,Germany:PhysicaVerlag,1998:107-121.
[4]Lin T Y.Granular computing on binary relations Ⅱ:Rough set representations and belief functions[A].Rough Sets and Knowledge Discovery[C].Heidelberg,Germany:PhysicaVerlag,1998:122-140.
[5]Pawlak Z.Rough sets[J].International Journal of Computer and Information Science,1982,11:341-356.
[6]Chen Yumin,Miao Duoqian,Wang Ruizhi.A rough set approach to feature selection based on ant colony optimization[J].Pattern Recognition Letters,2010,31(3):226-233.
[7]魏利华,唐振民,丁辉,等.不完备目标信息系统中基于差异关系的粗糙集[J].南京理工大学学报,2010,34(4):415-419. Wei Lihua,Tang Zhenmin,Ding Hui,et al.Discernibility relationbased rough set in incomplete decision system[J].Journal of Nanjing University of Science and Technology,2010,34(4):415-419.
[8]Qian Yuhua,Liang Jiye,Dang Chuangyin.Converse approximation and rule extraction from decision tables in rough set theory[J].Computers & Mathematics with Applications,2008,55(8):1754-1765.
[9]Shi Zhanhong,Gong Zengtai.The further investigation of coveringbased rough sets:Uncertainty characterization,similarity measure and generalized models[J].Information Sciences,2010,180(19):3745-3763.
[10]Dembczyński K,Greco S,Sowiński R.Rough set approach to multiple criteria classification with imprecise evaluations and assignments[J].European Journal of Operation Research,2009,198(2):626-636.
[11]Zhai Lianyin,Khoo L,Zhong Zhaowei.Design concept evaluation in product development using rough sets and grey relation analysis[J].Expert Systems with Applications,2009,36(3):7072-7079.
[12]Qian Yuhua,Liang Jiye,Li Deyu,et al.Measures for evaluating the decision performance of a decision table in rough set theory[J].Information Sciences,2008,178(1):181-202.
[13]杨习贝,杨静宇.邻域系统粗糙集模型[J].南京理工大学学报,2012,36(2):291-295. Yang Xibei,Yang Jingyu.Rough set model based on neighborhood system[J].Journal of Nanjing University of Science and Technology,2012,36(2):291-295.
[14]Qian Yuhua,Liang Jiye,Yao Yiyu,et al.MGRS:A multigranulation rough set[J].Information Sciences,2010,180(6):949-970.
[15]Qian Yuhua,Liang Jiye,Dang Chuangyin.Incomplete multigranulation rough set[J].IEEE Transactions on Systems,Man and Cybernetics,Part A,2010,40(2):420-431.
[16]Stefanowski J,Tsoukias A.On the extension of rough sets under incomplete information[A].Proceedings of the 7th international workshop on new directions in rough sets,data mining,and granularsoft computing[C].Berlin,Germany:SpringerVedag,1999,1711:73-81.
[17]张文修,米据生,吴伟志.不协调目标系统的知识约简[J].计算机学报,2003,26(1):12-18. Zhang Wenxiu,Mi Jusheng,Wu Weizhi.Knowledge reductions in inconsistent information systems[J].Chinese Journal of Computers,2003,26(1):12-18.
[18]Yang Xibei,Yang Jingyu,Wu Chen,et al.Dominancebased rough set approach and knowledge reductions in incomplete ordered information system[J].Information Sciences,2008,178(4):1219-1234.
[19]杨习贝,於东军,吴陈,等.不完备信息系统中基于相似关系的知识约简[J].计算机科学,2008,35(2):163-165,177. Yang Xibei,Yu Dongjun,Wu Chen,et al.Knowledge reductions in incomplete information systems based on similarity relation[J].Computer Sciences,2008,35(2):163-165,177.


Last Update: 2013-02-15