Fuzzy regression analysis: An application on tensile strength of materials and hardness scales

被引:4
作者
Karakasidis, T. E. [1 ]
Georgiou, D. N. [2 ]
Nieto, Juan J. [3 ]
机构
[1] Univ Thessaly, Dept Civil Engn, Volos 38334, Greece
[2] Univ Patras, Dept Math, GR-26110 Patras, Greece
[3] Univ Santiago Compostela, Dept Anal Matemat, Fac Matemat, Santiago De Compostela, Spain
关键词
Data analysis; fuzzy numbers; fuzzy linear regression models; metric spaces; hardness scale; tensile strength; LINEAR-REGRESSION; MODEL; SYSTEMS;
D O I
10.3233/IFS-2012-0507
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the present paper we use fuzzy linear regression analysis and fuzzy similarity to investigate the relation of various hardness scales to tensile strength of materials. We examine the relation of the Vickers, Brinell, Rockwell C and Shore Scleroscope hardness scales with tensile strength in a common measurement range. The fuzzy regression models that result show the existence of a linear relation. Further analysis of the resulting models with fuzzy similarity results indicates strong similarities between models of different hardness scales. The results indicate that this similarity of the fuzzy regression reflects the underling similarity of the physical quantities of materials that are measured on the different hardness scales. A comparison with conventional linear regression analysis shows that the ambiguities of the model are better reflected in the case of fuzzy regression models.
引用
收藏
页码:177 / 186
页数:10
相关论文
共 24 条
  • [1] Agrawal B.K., 1998, INTRO ENG MAT, P1
  • [2] Bardossy A., 1995, FUZZY RULE BASED MOD, P5
  • [3] BARDOSSY A, 1992, FUZZY REGRESSION ANA, P181
  • [4] Fuzzy regression-based mathematical programming model for quality function deployment
    Chen, Y
    Tang, J
    Fung, RYK
    Ren, Z
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2004, 42 (05) : 1009 - 1027
  • [5] Balancing productivity and consumer satisfaction for profitability: Statistical and fuzzy regression analysis
    He, Yan-Qun
    Chan, Lai-Kow
    Wu, Ming-Lu
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 176 (01) : 252 - 263
  • [6] A simple method for computation of fuzzy linear regression
    Hojati, M
    Bector, CR
    Smimou, K
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2005, 166 (01) : 172 - 184
  • [7] Fuzzy regression approach to modelling transfer moulding for microchip encapsulation
    Ip, KW
    Kwong, CK
    Wong, YW
    [J]. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2003, 140 : 147 - 151
  • [8] Least-squares estimates in fuzzy regression analysis
    Kao, C
    Chyu, CL
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2003, 148 (02) : 426 - 435
  • [9] Kuentai C., 2006, MATH COMPUT MODEL, V43, P809
  • [10] Fuzzy regression approach to process modelling and optimization of epoxy dispensing
    Kwong, CK
    Bai, H
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2005, 43 (12) : 2359 - 2375