1 |
Tseng, F. M., Tzeng, G. H., Yu, H. C. and Yuan, B. J. C. (2001). Fuzzy ARIMA model for forecasting the foreign exchange market, Fuzzy Sets and Systems, 118, 9-19
DOI
ScienceOn
|
2 |
Vapnik, V. (1995). The Nature of Statistical Learning Theory, Springer, Berlin
|
3 |
Vapnik, V. (1998). Statistical Learning Theory, John Wiley & Sons, New York
|
4 |
Watada, J. (1992). Fuzzy time series analysis and forecasting of sales volume, Fuzzy Regression Analysis, Omnitech Press, Warsaw and Physica-Verlag, Heidelberg, 211-227
|
5 |
West, M. and Harrison, P. J. (1997). Bayesian Forecasting and Dynamic Models, Springer-Verlag, New York
|
6 |
Zadeh, L. A. (1965). Fuzzy sets, Information and Control, 8, 338-353
DOI
|
7 |
Song, Q. and Chissom, B. S. (1993a). Fuzzy time-series and its models, Fuzzy Sets and Systems, 54, 269-277
DOI
ScienceOn
|
8 |
Song, Q. and Chissom, B. S. (1993b). Forecasting enrollments with fuzzy time series - part Ⅰ, Fuzzy Sets and Systems, 54, 1-9
DOI
ScienceOn
|
9 |
Song, Q. and Chissom, B. S. (1994). Forecasting enrollmenis with fuzzy time series - part Ⅱ, Fuzzy Sets and Systems, 62, 1-8
DOI
ScienceOn
|
10 |
Song, Q., Leland, R. P. and Chissom, B. S. (1995). A new fuzzy time-series model of fuzzy number observations, Fuzzy Sets and Systems, 73, 341-348
DOI
ScienceOn
|
11 |
Tanaka, H. (1987). Fuzzy data analysis by possibility linear models, Fuzzy Sets and Systems, 24, 363-375
DOI
ScienceOn
|
12 |
Tanaka, H. and Ishibuchi, H. (1992). Possibility regression analysis based on linear programming, Fuzzy Regression Analysis, 47-60
|
13 |
Tanaka, H. and Lee, H. (1998). Interval regression analysis by quadratic programming approach, IEEE Transactions on Fuzzy Systems, 6, 473-481
DOI
ScienceOn
|
14 |
Tanaka, H., Uejima, S. and Asai, K. (1982). Linear regression analysis with fuzzy model, IEEE Transactions on Systems Man Cybernetics, 12, 903-907
DOI
ScienceOn
|
15 |
Tsaur, R. C., Wang, H. F. and Yang, J. C. O. (2002). Fuzzy regression for seasonal time series analysis, International Journal of Information Technology & Decision Making, 1, 165-175
DOI
ScienceOn
|
16 |
Franses, P. H. (1998). Time Series Models for Business and Economic Forecasting, Cambridge Uni-versity Press, Cambridge
|
17 |
Tseng,F. M. and Tzeng, G. H. (2002). A fuzzy seasonal ARIMA model for forecasting, Fuzzy Sets and Systems, 126, 367-376
DOI
ScienceOn
|
18 |
Cherkassky, V., Shao, X., Muller, F. M. and Vapnik, V. N. (1999). Model complexity control for regression using VC generalization bounds, IEEE Transactions on Neural Networks, 10, 1075-1089
DOI
ScienceOn
|
19 |
Dominici, F., McDermott, A. and Hastie, T. J. (2004). Improved semi-parametric time series models of air pollution and mortality, Journal of the American Statistical Association, 99, 938-948
DOI
ScienceOn
|
20 |
Ghysels, E. and Osborn, D. R. (2001). The Econometric Analysis of Seasonal Time Series, Cambridge University Press, Cambridge
|
21 |
Haykin, S. and Kosko, B. (2001). Intelligent Signal Processing, Wiley-IEEE Press, New York
|
22 |
Hong, D. H. and Hwang, C. (2005). Interval regression analysis using quadratic loss support vector machine, IEEE Transactions on Fuzzy Systems, 13, 229-237
DOI
ScienceOn
|
23 |
Hwang, C., Hong, D. H. and Seok, K. H. (2006). Support vector interval regression machine for crisp input and output data, Fuzzy Sets and Systems, 157, 1114-1125
DOI
ScienceOn
|
24 |
Hwang, J. R., Chen, S. M. and Lee, C. H. (1998). Handling forecasting problems using fuzzy time series, Fuzzy Sets and Systems, 100, 217-228
DOI
ScienceOn
|
25 |
Montgomery, D. C., Johson, L. A. and Gardiner, J. S. (1990). Forecasting and Time Series Analysis, McGraw-Hill, New York
|
26 |
Chen, S. M. (1996). Forecasting enrollments based on fuzzy time series, Fuzzy Sets and Systems, 81, 311-319
DOI
ScienceOn
|
27 |
Smola, A. J., , T. T. and Scholkopf, B. (1998). Semiparametric support vector and linear pro-gramming machines, In Proceedings of the 1998 conference on Advances in Neural Information Processing Systems, 585-591
|
28 |
Box, G. P. and Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control, Holden-Day, San Francisco
|
29 |
Burman, P. and Shumway, R. (1998). Semiparametric modeling of seasonal time series, Journal of Time Series Analysis, 19, 127-145
DOI
ScienceOn
|
30 |
Chang, P. T. (1997). Fuzzy seasonality forecasting, Fuzzy Sets and Systems, 90, 1-10
DOI
ScienceOn
|