An Advanced Approach to Forecasting Tourism Demand in Taiwan

REFERENCES

• Canestrelli , E. and Costa , P. 1991 . Tourist carrying capacity: A fuzzy approach . Annals of Tourism Research , 18 : 295 – 311 .
   Web of Science ®Google Scholar
• Chen , S.-M. 1996 . Forecasting enrollments based on fuzzy time series . Fuzzy Sets and Systems , 81 : 311 – 319 .
   Web of Science ®Google Scholar
• Chen , S.-M. and Hwang , J. R. 2000 . Temperature prediction using fuzzy time series . IEEE Trans. Syst. Man Cybern. Part B , 30 ( 2 ) : 263 – 275 .
   PubMed Web of Science ®Google Scholar
• Dickey , D. A. and Fuller , W. A. 1979 . Distribution of the estimates for autoregressive time series with a unit root . Journal of the American Statistical Association , 74 : 427 – 431 .
   Web of Science ®Google Scholar
• Du Preez , J. and Witt , S. F. 2003 . Univariate versus multivariate time series forecasting: an application to international tourism demand . International Journal of Forecasting , 19 : 435 – 451 .
   Web of Science ®Google Scholar
• Fuller , W. 1976 . Introduction to Statistical Time Series , New York : Wiley .
   Google Scholar
• Funahashi , K. 1989 . On the approximate realization of continuous mappings by neural networks . Neural Networks , 2 : 183 – 192 .
   Web of Science ®Google Scholar
• Granger , C. W. J. and Newbold , P. 1974 . Spurious regressions in econometrics . Journal of Econometrics , 2 : 111 – 120 .
   Google Scholar
• Hornik , K. 1993 . Some new results on neural network approximation . Neural Networks , 6 : 1069 – 1072 .
   Web of Science ®Google Scholar
• Huarng , K. 2001 . Heuristic models of fuzzy time series for forecasting . Fuzzy Sets and Systems , 123 ( 3 ) : 369 – 386 .
   Web of Science ®Google Scholar
• Huarng , K. and Yu , H.-K. 2006 . The application of neural networks to forecast fuzzy time series . Physica A: Statistical Mechanics and Its Applications , 363 : 481 – 491 .
   Web of Science ®Google Scholar
• 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 .
   Web of Science ®Google Scholar
• Indro , D. C. , Jiang , C. X. , Patuwo , B. E. and Zhang , G. P. 1999 . Predicting mutual fund performance using artificial neural networks . Omega Int. J. Manage. Sci. , 27 : 373 – 380 .
   Web of Science ®Google Scholar
• Kwiatkowski , D. , Phillips , P. C.B. , Schmidt , P. and Shin , Y. 1992 . Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? . Journal of Econometrics , 54 : 159 – 178 .
   Web of Science ®Google Scholar
• Law , R. 2000 . Back-propagation learning in improving the accuracy neural network-based tourism demand forecasting . Tourism Management , 21 : 331 – 340 .
   Web of Science ®Google Scholar
• Law , R. and Au , N. 1999 . A neural network model to forecast Japanese demand for travel to Hong Kong . Tourism Management , 20 : 89 – 97 .
   Web of Science ®Google Scholar
• MacKinnon , J. G. 1991 . “ Critical values for cointegration tests ” . In Long Run Economic Relationships: Readings in Cointegration , Edited by: Engle , R. F. and Granger , C. W.J. 267 – 276 . Oxford University Press .
   Google Scholar
• Phillips , P. C. B. and Perron , P. 1988 . Testing for a unit root in time series regression . Biometrika , 75 : 335 – 346 .
   Web of Science ®Google Scholar
• Rumelhart , B. D. and Lehr , M. A. 1994 . Neural networks: Applications in industry, business and science . Communications of the ACM , 37 ( 3 ) : 93 – 105 .
   Web of Science ®Google Scholar
• Smith , K. A. and Gupta , J. N.D. 2002 . Neural Networks in Business: Techniques and Applications , Hershey : PA Idea Group Publishing .
   Google Scholar
• Song , Q. and Chissom , B. S. 1993a . Forecasting enrollments with fuzzy time series-Part 1 . Fuzzy Sets and Systems , 54 : 1 – 9 .
   Web of Science ®Google Scholar
• Song , Q. and Chissom , B. S. 1993b . Fuzzy time series and its models . Fuzzy Sets and Systems , 54 : 269 – 277 .
   Web of Science ®Google Scholar
• Song , Q. and Chissom , B. S. 1994 . Forecasting enrollments with fuzzy time series-Part 2 . Fuzzy Sets and Systems , 62 : 1 – 8 .
   Web of Science ®Google Scholar
• Sullivan , J. and Woodall , W. H. 1994 . A comparison of fuzzy forecasting and Markov modeling . Fuzzy Sets and Systems , 64 : 279 – 293 .
   Web of Science ®Google Scholar
• Wang , C.-H. 2004 . Predicting tourism demand using fuzzy time series and hybrid grey theory . Tourism Management , 25 : 367 – 374 .
   Web of Science ®Google Scholar
• Wasserman , P. D. 1989 . Neural Computing: Theory and Practice , New York, NY : Van Nostrand Reinhold .
   Google Scholar
• Widrow , B. , Rumelhart , D. E. and Lehr , M. A. 1994 . Neural networks: applications in industry, business and science . Communications of the ACM , 37 ( 3 ) : 93 – 105 .
   Web of Science ®Google Scholar
• Yu , H.-K. 2005 . A refined fuzzy time-series model for forecasting . Physica A: Statistical Mechanics and Its Applications , 346 ( 3–4 ) : 657 – 681 .
   Google Scholar
• Zhang , G. , Patuwo , B. E. and Hu , M. Y. 1998 . Forecasting with artificial neural networks: The state of the art . International Journal of Forecasting , 14 : 35 – 62 .
   Web of Science ®Google Scholar