Emergent rough set data analysis

被引:0
|
作者
Hassan, Y [1 ]
Tazaki, E [1 ]
机构
[1] Toin Univ Yokohama, Dept Control & Syst Engn, Aoba Ku, Yokohama, Kanagawa 2258502, Japan
来源
TRANSACTIONS ON ROUGH SETS II: ROUGH SETS AND FUZZY SETS | 2004年 / 3135卷
关键词
rough sets; emergent behavior; reduct; rule induction; discretization;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Many systems in nature produce complicated behaviors, which emerge from the local interactions of relatively simple individual components that live in some spatially extended world. Notably, this type of emergent behavior formation often occurs without the existence of a central control. The rough set concept is a new mathematical approach to imprecision, vagueness and uncertainty. This paper introduces the emergent computational paradigm and discusses its applicability and potential in rough sets theory. In emergence algorithm, the overall System dynamics emerge from the local interactions of independent objects or agents. For accepting a system is displaying an emergent behavior, the system should be constructed by describing local elementary interactions between components in different ways than those used in describing global behavior and properties of the running system over a period of time. The proposals of an emergent computation structure for implementing basic rough sets theory operators are also given in this paper.
引用
收藏
页码:343 / 361
页数:19
相关论文
共 50 条
  • [41] Rough Sets Meet Statistics - A New View on Rough Set Reasoning About Numerical Data
    Palangetic, Marko
    Cornelis, Chris
    Greco, Salvatore
    Slowinski, Roman
    ROUGH SETS, IJCRS 2020, 2020, 12179 : 78 - 92
  • [42] Rough Set Approach in Ultrasound Biomicroscopy Glaucoma Analysis
    Banerjee, Soumya
    Al-Qaheri, Hameed
    El-Dahshan, El-Sayed A.
    Hassanien, Aboul Ella
    ADVANCES IN COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, PROCEEDINGS, 2010, 6059 : 491 - +
  • [43] Conflict analysis and information systems: A rough set approach
    Skowron, Andrzej
    Ramanna, Sheela
    Peters, James F.
    ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS, 2006, 4062 : 233 - 240
  • [44] The relationships between the inclusion degree and measures on rough set data analysis based on regular probability spaces
    Tsang, Eric C. C.
    Yang, Wen-Xia
    Chen, De-Gang
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 2412 - +
  • [45] In the context of multiple intelligences theory, intelligent data analysis of learning styles was based on rough set theory
    Narli, Serkan
    Ozgen, Kemal
    Alkan, Huseyin
    LEARNING AND INDIVIDUAL DIFFERENCES, 2011, 21 (05) : 613 - 618
  • [46] A generalized rough set-based information filling technique for failure analysis of thruster experimental data
    Han Shan
    Zhu Qiang
    Li Jianxun
    Chen Lin
    CHINESE JOURNAL OF AERONAUTICS, 2013, 26 (05) : 1182 - 1194
  • [47] Novel Approach to Tourism Analysis with Multiple Outcome Capability Using Rough Set Theory
    Huang, Chun-Che
    Tseng, Tzu-Liang
    Chen, Kun-Cheng
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2016, 9 (06) : 1118 - 1132
  • [48] Novel Approach to Tourism Analysis with Multiple Outcome Capability Using Rough Set Theory
    Chun-Che Huang
    Tzu-Liang Bill Tseng
    Kun-Cheng Chen
    International Journal of Computational Intelligence Systems, 2016, 9 : 1118 - 1132
  • [49] Rule induction based on an incremental rough set
    Fan, Yu-Neng
    Tseng, Tzu-Liang
    Chern, Ching-Chin
    Huang, Chun-Che
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (09) : 11439 - 11450
  • [50] Attribute Selection for Partially Labeled Categorical Data By Rough Set Approach
    Dai, Jianhua
    Hu, Qinghua
    Zhang, Jinghong
    Hu, Hu
    Zheng, Nenggan
    IEEE TRANSACTIONS ON CYBERNETICS, 2017, 47 (09) : 2460 - 2471