1 |
Chen, Y. (1999), Fuzzy ranking and quadratic fuzzy regression. Computers and Mathematics with Applications, Vol. 38, 265-279
DOI
ScienceOn
|
2 |
Diamond, P. (1988), Fuzzy least squares. Information Science, Vol. 46, 141-157
DOI
ScienceOn
|
3 |
Hong, D.H. and Hwang, C. (2004). Support vector Machine for Internal Regression. Proceeding of Autumn Conference on Korean Statistical Society, 67-72
|
4 |
Hong, D.H. and Hwang, C. (2005). Internal regression analysis using quadratic loss support vector machine. IEEE Transactions on Fuzzy Systems, Vol. 13, 229-237
DOI
ScienceOn
|
5 |
Inuiguchi, M., Fujita, H. and Tanino, T. (2001). Interval linear regression analysis bases on Minkowski difference, Proceeding of International Conference on Information Systems. Analysis and Synthesis, Vol. 7, 112-117
|
6 |
Ishibuchi, H. and Tanaka, H. (1992). Fuzzy regression analysis using neural networks. Fuzzy sets and Systems, Vol. 50, 57-65
|
7 |
Jeng, J,T., Chuang, C. and Su, S.F. (2003). Support vector interval regression networks for interval regression analysis. Fuzzy Sets and Systems, Vol. 138, 283-300
DOI
ScienceOn
|
8 |
Lee, H. and Tanaka, H. (1999). Upper and lower approximation models in interval regression using regression quantile techniques. European Journal of Operational Research, Vol. 116, 653-666
DOI
ScienceOn
|
9 |
Tanaka, H., Hayashi, I. and Watada, J. (1987). Interval regression analysis. Third Fuzzy System Symposium, 9-12
|
10 |
Tanaka, H. and Lee, H. (1998). Interval regression analysis by quadratic programming approach. IEEE Transactions on Fuzzy Systems, Vol. 6, 473-481
DOI
ScienceOn
|
11 |
Hwang, S.G. and Seo, Y.J. (1989). 제약부 구간 선형 회귀모델에 의한 실동시간의 견적. Journal of the Korean OR/MS Society, Vol. 14, 105-114
|