Reduction method based on a new fuzzy rough set in fuzzy information system and its applications to scheduling problems

被引:13
|
作者
Liu, Min [1 ]
Chen, Degang
Wu, Cheng
Li, Hongxing
机构
[1] Tsing Hua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] N China Elect Power Univ, Dept Math & Phys, Beijing 102206, Peoples R China
[3] Beijing Normal Univ, Dept Math, Beijing 100875, Peoples R China
基金
中国国家自然科学基金;
关键词
fuzzy rough set; fuzzy information granule; fuzzy information system; reduction; scheduling;
D O I
10.1016/j.camwa.2005.10.017
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, we present the concept of fuzzy information granule based on a relatively weaker fuzzy similarity relation called fuzzy T-L-similarity relation for the first time. Then, according to the fuzzy information granule, we define the lower and upper approximations of fuzzy sets and a corresponding new fuzzy rough set. Furthermore. we construct a kind of new fuzzy information system based on the fuzzy T-L-similarity relation and study its reduction using the fuzzy rough set. At last, we apply the reduction method based on the defined fuzzy rough set in the above fuzzy information system to the reduction of the redundant multiple fuzzy rule in the scheduling problems, and numerical computational results show that the reduction method based on the new fuzzy rough set is more suitable for the reduction of multiple fuzzy rules in the scheduling problems compared with the reduction methods based on the existing fuzzy rough set. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1571 / 1584
页数:14
相关论文
共 50 条
  • [41] Research on fuzzy rough parallel reduction based on mutual information
    Xu, F. (xufeifei@shiep.edu.cn), 1600, Binary Information Press (10):
  • [42] Applications of probabilistic hesitant fuzzy rough set in decision support system
    Khan, Muhammad Ali
    Ashraf, Shahzaib
    Abdullah, Saleem
    Ghani, Fazal
    SOFT COMPUTING, 2020, 24 (22) : 16759 - 16774
  • [43] Applications of probabilistic hesitant fuzzy rough set in decision support system
    Muhammad Ali Khan
    Shahzaib Ashraf
    Saleem Abdullah
    Fazal Ghani
    Soft Computing, 2020, 24 : 16759 - 16774
  • [44] Two new operators in rough set theory with applications to fuzzy sets
    Zhang, HG
    Liang, HL
    Liu, DR
    INFORMATION SCIENCES, 2004, 166 (1-4) : 147 - 165
  • [45] Distance-based rough set model in intuitionistic fuzzy information systems and its application
    Huang, Bing
    Wei, Da-Kuan
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2011, 31 (07): : 1356 - 1362
  • [46] AFS fuzzy logic system and its applications to fuzzy information processing
    Liu, Xiao-Dong
    Zhang, Qing-Ling
    Wang, Yan
    Dongbei Daxue Xuebao/Journal of Northeastern University, 2002, 23 (04): : 321 - 324
  • [47] Attribute reduction for hierarchical classification based on improved fuzzy rough set
    Yang, Jie
    Qin, Xiaodan
    Wang, Guoyin
    Zhang, Qinghua
    Li, Shuai
    Wu, Di
    INFORMATION SCIENCES, 2024, 677
  • [48] Reduction algorthims for hybrid data based on fuzzy rough set approaches
    Hu, QH
    Yu, DR
    Xie, ZX
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 1469 - 1474
  • [49] Fuzzy rough set attribute reduction based on decision ball model
    Ji, Xia
    Duan, Wanyu
    Peng, Jianhua
    Yao, Sheng
    INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2025, 179
  • [50] Unsupervised fuzzy-rough set-based dimensionality reduction
    Mac Parthalain, Neil
    Jensen, Richard
    INFORMATION SCIENCES, 2013, 229 : 106 - 121