EVALUATION OF FUZZY LINEAR-REGRESSION MODELS

被引:185
作者
SAVIC, DA [1 ]
PEDRYCZ, W [1 ]
机构
[1] UNIV MANITOBA,DEPT ELECT ENGN,WINNIPEG R3T 2N2,MANITOBA,CANADA
关键词
FUZZY REGRESSION; FUZZY LINEAR REGRESSION; IDENTIFICATION; PREDICTION;
D O I
10.1016/0165-0114(91)90065-X
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Fuzzy linear regression provides means for tackling regression problems lacking a significant amount of data for determining regression models and with vague relationships between the dependent variable and independent variables. In the paper a two-stage construction of a linear regression model is proposed using an enhancement of a minimal vagueness criterion already discussed in fuzzy regression analysis. Two different experiments are set up and used for evaluating both models. The choice of the fuzzy regression model should be made in the context of a practical application.
引用
收藏
页码:51 / 63
页数:13
相关论文
共 11 条
[1]   NOTE ON FUZZY REGRESSION [J].
BARDOSSY, A .
FUZZY SETS AND SYSTEMS, 1990, 37 (01) :65-75
[2]  
DIAMOND P, 1987, 2ND INT C INT FUZZ S
[3]  
Dubois, 1980, FUZZY SETS FUZZY SYS
[4]  
KLEINBAUM DG, 1978, APPLIED REGRESSION A
[5]  
NETER J, 1985, APPLIED LINEAR STATI
[6]   FUZZY DATA-ANALYSIS BY POSSIBILISTIC LINEAR-MODELS [J].
TANAKA, H .
FUZZY SETS AND SYSTEMS, 1987, 24 (03) :363-375
[7]  
TANAKA H, 1982, IEEE T SYST MAN CYB, P903
[8]  
TANAKA H, 1988, FUZZY SETS SYSTEMS, V27, P1
[9]  
TANAKA H, 1980, INT C APPLIED SYSTEM
[10]  
WATADA J, 1983, THESIS U OSAKA PREFE