Data Mining Approach for Ship Virtual Assembly based on Rough Set Theory

被引：0
|
作者：
Li, Cuiling [1 ]
Zhao, Rongyong [2 ]
Xiang, Yang [1 ]
Xu, Shanlin [1 ]
机构：
[1] Shanghai Maritime Univ, Elect Engn & Automat Dept, Shanghai 200135, Peoples R China
[2] Tongji Univ, CIMS Res Ctr, Shanghai 200092, Peoples R China
来源：
2008 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, VOLS 1 AND 2, PROCEEDINGS | 2008年
关键词：
data mining; rough set theory; shipbuilding; virtual assembly; Petri net;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
To discover process planning knowledge for ship virtual assembly, a novel data mining approach is proposed based on rough set theory. The present achievements about data mining with rough set theory and virtual assembly technology for shipbuilding are studied respectively The current Petri net model for ship assembly is analyzed. A new transform? model from Petri net to rough set theory is presented. Thereby a systematical approach is proposed based on the present process planning platform for shipbuilding and three dimension virtual assembly software. Finally, a data mining example from engineering of ship engine assembly illustrates that this approach is feasible. Some meaningful assembly knowledge is discovered. The dependence on operational experience of human-being can be reduced and the efficiency of ship virtual assembly can be enhanced obviously
引用
收藏
页码：691 / +
页数：2
相关论文
共 50 条
  • [21] Integrated approach to data mining based on rough set and neural network
    Lu, Guang-Hui
    Xiao, Ren-Bin
    Xiaoxing Weixing Jisuanji Xitong/Mini-Micro Systems, 2002, 23 (05):
  • [22] Incomplete data analysis approach based on Rough set theory
    Zhang, Wei
    Liao, Xiaofeng
    Wu, Zhongfu
    Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence, 2003, 16 (02):
  • [23] A rough set approach to attribute generalization in data mining
    Chan, CC
    INFORMATION SCIENCES, 1998, 107 (1-4) : 169 - 176
  • [24] Mining of microRNA expression data - A rough set approach
    Fang, Jianwen
    Grzymala-Busse, Jerzy W.
    ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS, 2006, 4062 : 758 - 765
  • [25] Mining Incomplete Data-A Rough Set Approach
    Grzymala-Busse, Jerzy W.
    ROUGH SETS AND KNOWLEDGE TECHNOLOGY, 2011, 6954 : 1 - 7
  • [26] Design and implementation of commerce data mining system based on Rough Set theory
    Xiang, Y
    Wu, WY
    Mao, HR
    Song, QW
    ICEBE 2005: IEEE INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING, PROCEEDINGS, 2005, : 258 - 265
  • [27] A new data mining approach combined with extension set and rough set
    Tang, Zhi-Hang
    Tian, Wen-Bin
    Journal of Software, 2014, 9 (02) : 451 - 457
  • [28] A new data mining approach for fault diagnosis of high voltage transmission line based on rough set theory
    Liao, Z.
    Sun, Y.
    Dianli Xitong Zidonghue/Automation of Electric Power Systems, 2001, 25 (15): : 15 - 19
  • [29] Rough set theory: Application in electronic commerce data mining
    Wang, XR
    Xu, RS
    Wang, WS
    IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2004), PROCEEDINGS, 2004, : 541 - 544
  • [30] Rough set theory: A data mining tool for semiconductor manufacturing
    Kusiak, A
    IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANUFACTURING, 2001, 24 (01): : 44 - 50
12345