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
来源
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
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
  • [31] Multi-agent cooperation method based on intention recognition
    Liu Lin
    Wang Yuehuan
    CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 4, PROCEEDINGS, 2008, : 216 - 219
  • [32] Method for Subway Operation Adjustment Based on Multi-Agent
    Lu, Fei
    Zhang, Zhihui
    2009 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS ( ICAL 2009), VOLS 1-3, 2009, : 1189 - 1193
  • [33] Clustering in a Multi-Agent Data Mining Environment
    Chaimontree, Santhana
    Atkinson, Katie
    Coenen, Frans
    AGENTS AND DATA MINING INTERACTION, 2010, 5980 : 103 - 114
  • [34] RESEARCH ON KNOWLEDGE EXPRESSING METHOD BASED ON MULTI-AGENT
    Ai, Dongmei
    Wen, Jing
    Ning, Shurong
    Ban, Xiaojuan
    CIICT 2008: PROCEEDINGS OF CHINA-IRELAND INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATIONS TECHNOLOGIES 2008, 2008, : 155 - +
  • [35] Decentralized multi-agent optimization based on a penalty method
    Konnov, I., V
    OPTIMIZATION, 2022, 71 (15) : 4529 - 4553
  • [36] Mining the Association of Multiple Virtual Identities Based on Multi-Agent Interaction
    Li, Le
    Xiao, Weidong
    Dai, Changhua
    Tong, Haiming
    Song, Zhiqiang
    DATABASES THEORY AND APPLICATIONS, ADC 2014, 2014, 8506 : 172 - 179
  • [37] A community mining algorithm for web texts based on Multi-agent system
    Yang, Hui
    Wang, Zhe
    Zhou, Xu
    Zhou, Tong
    Wang, Zuo
    Journal of Computational Information Systems, 2010, 6 (11): : 3509 - 3516
  • [38] A multi-agent based method for handling exceptions in CSCD
    Tian, F
    Li, RH
    Abdulrahman, MD
    Zhang, JC
    PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN, VOL 1, 2004, : 297 - 302
  • [39] Method for subway operation adjustment based on multi-agent
    School of Control Science and Engineering, Shandong University, Jinan 250061, China
    Zhongguo Tiedao Kexue, 2007, 1 (123-126):
  • [40] 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