A Multi-Agent method for parallel mining based on rough sets

被引:0
|
作者
Geng, Zhiqiang [1 ]
Zhu, Qunxiong [1 ]
机构
[1] Beijing Univ Chem Technol, Sch Informat Sci & Technol, Beijing 100029, Peoples R China
关键词
rough set; data mining; Multi-agent; parallel mining;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Rough set is a relatively new AI technique in data mining. Multi-Agent system (MAS) has become a hotspot in the field of distributed AI recently. The challenge of the information age yet has not been resolved and the decision can't be made precisely and in time according to market and requirements. To improve the performing efficiency of data mining system, the paper defines the novel operations and reasoning of agents and a Multi-Agent method for parallel rule mining based on Rough sets is proposed. The information system is decomposed into many sub-information systems and every sub-information system can be an agent using rough set to acquire rules. From results of parallel mining, decisions can be made quickly and precisely.
引用
收藏
页码:5977 / +
页数:2
相关论文
共 50 条
  • [41] Process mining of a multi-agent business simulator
    Ito, Sohei
    Vymetal, Dominik
    Sperka, Roman
    Halaska, Michal
    COMPUTATIONAL AND MATHEMATICAL ORGANIZATION THEORY, 2018, 24 (04) : 500 - 531
  • [42] Multi-agent systems and distributed data mining
    Giannella, C
    Bhargava, R
    Kargupta, H
    COOPERATIVE INFORMATION AGENTS VIII, PROCEEDINGS, 2004, 3191 : 1 - 15
  • [43] A multi-agent based micro grid operation method
    Nagata, Takeshi
    Kato, Kosuke
    Utatani, Masahiro
    Ueda, Yuji
    Okamoto, Kazuya
    Nagata, Chihiro
    IEEJ Transactions on Electronics, Information and Systems, 2013, 133 (09) : 1652 - 1657
  • [44] A multi-agent based new cooperation method in CSCD
    An, YS
    Li, RH
    PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN, VOL 2, 2004, : 239 - 243
  • [45] Process mining of a multi-agent business simulator
    Sohei Ito
    Dominik Vymětal
    Roman Šperka
    Michal Halaška
    Computational and Mathematical Organization Theory, 2018, 24 : 500 - 531
  • [46] A fuzzy search method for rough sets in data mining
    Adjei, O
    Chen, L
    Cheng, HD
    Cooley, DH
    Cheng, RJ
    Twombly, X
    JOINT 9TH IFSA WORLD CONGRESS AND 20TH NAFIPS INTERNATIONAL CONFERENCE, PROCEEDINGS, VOLS. 1-5, 2001, : 980 - 985
  • [47] Adapting granular rough theory to multi-agent context
    Chen, B
    Zhou, MT
    ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING, 2003, 2639 : 701 - 705
  • [48] The Semantics of Norms Mining in Multi-agent Systems
    Mahmoud, Moamin A.
    Ahmad, Mohd Sharifuddin
    Ahmad, Azhana
    Yusoff, Mohd Zaliman Mohd
    Mustapha, Aida
    COMPUTATIONAL COLLECTIVE INTELLIGENCE - TECHNOLOGIES AND APPLICATIONS, PT I, 2012, 7653 : 425 - 435
  • [49] A Communication Schema for Parallel and Distributed Multi-agent Systems Based on MPI
    Rousset, Alban
    Herrmann, Benedicte
    Lang, Christophe
    Philippe, Laurent
    EURO-PAR 2015: PARALLEL PROCESSING WORKSHOPS, 2015, 9523 : 442 - 453
  • [50] A CGS-MSM Parallel Genetic Algorithm based on Multi-Agent
    zhao, Tinghong
    Man, Zibin
    Wan, Zhijun
    Bi, Guiquan
    SECOND INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING: WGEC 2008, PROCEEDINGS, 2008, : 10 - 13