Mathematical formulation of knitted fabric spirality using genetic programming

Textile Research Journal

Volumn 82, Issue 7, 2012, Pages 667-676

  Chen, Zeng Hai ^a   xu, Bin Gang ^a   Chi, Zhe ru ^a   Feng, Da Gan ^a,b  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b UNIVERSITY OF SYDNEY   (Australia)

Author keywords

computational intelligence; fabric spirality; Genetic programming; multiple linear regression

Indexed keywords

ARTIFICIAL INTELLIGENCE; GENETIC ALGORITHMS; INTELLIGENT COMPUTING; KNIT FABRICS; LINEAR REGRESSION; WOOL; YARN;

FABRIC PARAMETERS; MATHEMATICAL FORMULATION; MATHEMATICAL RELATIONSHIP; MULTIPLE LINEAR REGRESSION APPROACHES; MULTIPLE LINEAR REGRESSIONS; MULTIPLE REGRESSIONS; ROTATIONAL DIRECTIONS; SPIRALITY;

GENETIC PROGRAMMING;

EID: 84863257812     PISSN: 00405175     EISSN: 17467748     Source Type: Journal    
DOI: 10.1177/0040517511435011     Document Type: Article

References (22)

1. Gharehaghaji AA, Shanbeh M, Palhang M. Analysis of two modeling methodologies for predicting the tensile properties of cotton-covered nylon core yarns. Textile Res J 2007; 77(8): 565–571.
2. Pattanayak AK, Luximon A, Khandual A. Prediction of drape profile of cotton woven fabrics using artificial neural network and multiple regression method. Textile Res J 2011; 81(6): 559–566.
3. Shyr TW, Lai SS, Lin JY. New approaches to establishing translation equations for the total hand value of fabric. Textile Res J 2004; 74(6): 528–534.
4. Li M, Li DP, Zhang WY and Tang XZ. A multiple regression model for predicting comfort sensation of knitted fabric in sports condition based on objective properties. Proceedings of the Second International Conference on Information and Computing Science. 2009, pp.372–375.
5. Khan Z, Lim AEK, Wang LI, Wang XG, Beltran R. An artificial neural network-based hairiness prediction model for worsted wool yarns. Textile Res J 2009; 79(8): 714–720.
6. Lin JJ. A genetic algorithm-based solution search to fuzzy logical inference for breakdown causes in fabric inspection. Textile Res J 2009; 79(5): 394–409.
7. Admuthe LS, Apte S. Adaptive neuro-fuzzy inference system with subtractive clustering: a model to predict fiber and yarn relationship. Textile Res J 2010; 80(9): 841–846.
8. Hadizadeh M, Jeddi AAA, Tehran MA. The prediction of initial load-extension behavior of woven fabrics using artificial neural network. Textile Res J 2009; 79(17): 1599–1609.
9. Lau YM, Tao XM, Dhingra RC. Spirality in single jersey fabrics. Textile Asia 1995; 8: 95–102.
10. Tao J, Dhingra RC, Chan CK, Abbas MS. Effects of yarn and fabric construction on spirality of cotton single jersey fabrics. Textile Res J 1997; 67(1): 57–68.
11. Chen QH, Au KF, Yuen CWM, Yeung KW. Effects of yarn and knitting parameters on the spirality of plain knitted wool fabrics. Textile Res J 2003; 73(5): 421–426.
12. Murrells CM, Tao XM, Xu BG, Cheng KPS. An artificial neural network model for the prediction of spirality of fully relaxed single jersey fabrics. Textile Res J 2009; 79(3): 227–234.
13. Murrells CM. Twist liveliness of spun yarns and the effects on knitted fabric spirality. PhD Thesis, The Hong Kong Polytechnic University, Hong Kong, 2007.
14. Ekart A. Genetic programming for the design of lace knitting stitch patterns. Appl Innovations Intell Syst Xv 2008; 7: 261–274.
15. Dubrovski PD, Brezocnik M. Using genetic programming to predict the macroporosity of woven cotton fabrics. Textile Res J 2002; 72(3): 187–194.
16. Searson DP. GPTIPS: Genetic programming & symbolic regression for MATLAB. http://gptips.sourceforge.net/ (2010).
17. Tao XM and Xu BG. Manufacturing method and apparatus for torque-free singles ring yarns. US Patent 6,860,095, 2005.
18. Tao XM, Xu BG and Wong SK. Method and apparatus for manufacturing a singles ring yarn. US Patent 7,096,655, 2006.
19. Yang K, Tao XM, Xu BG, Lam J. Structure and properties of low twist short-staple singles ring spun yarns. Textile Res J 2007; 77(9): 675–685.
20. Hua T, Tao XM, Cheng KPS, Xu BG. Effects of geometry of ring spinning triangle on yarn torque: Part II: distribution of fiber tension within a yarn and its effects on yarn residual torque. Textile Res J 2010; 80(2): 116–123.
21. Tang HB, Xu BG, Tao XM. A new analytical solution of the twist wave propagation equation with its application in a modified ring spinning system. Textile Res J 2010; 80(7): 636–641.
22. Ong CS, Huang JJ, Tzeng GH. Building credit scoring models using genetic programming. Expert Syst Appl 2005; 29(1): 41–47.