A variable precision rough set based modeling method for pulsed GTAW

International Journal of Advanced Manufacturing Technology

Volumn 36, Issue 11-12, 2008, Pages 1072-1079

  Li, W H ^a   Chen, S B ^a   Wang, B ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

GTAW; Modeling; Variable precision rough set (VPRS); Welding process

Indexed keywords

MATHEMATICAL MODELS; NEURAL NETWORKS; PRECISION ENGINEERING; PROBLEM SOLVING; ROUGH SET THEORY;

FIELD OF ARC WELDING; GAS TUNGSTEN ARC WELDING (GTAW); VARIABLE PRECISION ROUGH SET (VPRS); WELDING MEDIA;

GAS METAL ARC WELDING;

EID: 43449098175     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-006-0922-7     Document Type: Article

References (17)

1. Chen SB (2000) Intelligent methodology for sensing, modeling and control of pulsed GTAW: Part I - Bead-on-plate welding. Weld J 79(6):151S-163S
2. Wang B, Chen SB, Wang JJ (2005) Rough set based knowledge modeling for the aluminum alloy pulsed GTAW process. Int J Adv Manuf Technol 25(9-10):902-908
3. Di L (2001) "Neural-network-based self-organized fuzzy logic control for arc welding". Eng Appl Artif Intell 14(2):115-124
4. Zhang GJ, Chen SB, Wu L (2005) Neural network modeling and system simulating for the dynamic process of varied gap pulsed GTAW with wire filler. J Mater Sci Technol 21(4):515-520
5. Christensen KH, Sorensen T (2003) A neural network approach for GMA butt joint welding. Intern J Join Mater 15(4):1-7
6. Fernandes PE (2002) Artificial neural networks applied to the tubular electrode arc welding process: modeling of the weld bead geometry. Metal Mater ABM 58:9-13
7. Hirai A (2003) Neural network model of weld pool in pulsed MIG welding. Quarterly J Japan Weld Soc 21(2):227-233
8. Ziarko W (1993) Variable precision rough set model. J Comput Syst Sci 46(1):39-59
9. Pawlak Z (1991) Rough sets-Theoretical aspects of reasoning about data. Kluwer, Dordrecht
10. Beynon MJ, Peel MJ (2001) Variable precision rough set theory and data discretisation: an application to corporate failure prediction. Omega-International J Manage Sci 29(6):561-576
11. An AJ (1996) Discovering rules for water demand prediction: An enhanced rough-set approach. Eng Appl Artif Intell 9(6):645-653
12. Wong SKM, Ziarko W (1985) "On optimal rules in decision tables". Bull Pol Acad Sci, Math 33:693-696
13. Skowron A, Rauszer C (1992) The discernibility matrices and functions in information systems. Intelligent decision support-handbook of application and advances of the Rough Sets Theory. Kluwer, Dordrecht
14. Wang B, Chen S (2002) Reduction and minimal set cover. J Shanghai Jiaotong Univ 36:106-108
15. Chen SB (2004) Welding robotic systems with visual sensing and real-time control of dynamic weld pool during pulsed GTAW. Int J Robot Autom 19(1):28-35
16. Fayyad UM, Irani KB (1993) Multi-interval discretization of continuous-valued attributes for classification learning. Proc Thirteenth International Joint Conference on Artificial Intelligence 2
17. Li WH, Chen SB, Lin T (2006) The comparison of discretization method in rough set based modeling method for welding. J Shanghai Jiaotong Univ 40(7):1094-1097