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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/110320 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/110320 http://eprints.org/relation/ismediumThumbnailVersionOf https://pure.iiasa.ac.at/id/document/110320 110326 2 334223 document 110326 small.jpg image/png 345772516a6119922011ed7f8ec9e1d8 MD5 1995 2025-07-02 12:41:59 https://pure.iiasa.ac.at/id/eprint/20728/6/small.jpg 20728 6 6 image/png other Thumbnails conversion from text to thumbnail_small en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/110320 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/110320 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/110320 archive 353 disk0/00/02/07/28 2025-07-02 12:32:37 2025-07-02 12:32:37 2025-07-02 12:32:37 article show Fang Y. Silva E.S. Guan B. Hassani H. 9469 Heravi S. pub ASA CAT empirical ensemble mode decomposition; tourism demand; time series analysis; forecast combination; decomposition; Japan This study introduces a novel forecast combination method for monthly Japanese tourism demand, analyzed at both aggregated and disaggregated levels, including tourist, business, and other travel purposes. The sample period spans from January 1996 to December 2018. Initially, the time series data were decomposed into high and low frequencies using the Ensemble Empirical Mode Decomposition (EEMD) technique. Following this, Autoregressive Integrated Moving Average (ARIMA), Neural Network (NN), and Support Vector Machine (SVM) forecasting models were applied to each decomposed component individually. The forecasts from these models were then combined to produce the final predictions. Our findings indicate that the two-stage forecast combination method significantly enhances forecasting accuracy in most cases. Consequently, the combined forecasts utilizing EEMD outperform those generated by individual models. 2025-05-07 published doi:10.3390/tourhosp6020079 3410 public Tourism and Hospitality 6 2 e79 1 TRUE 2673-5768 info:eu-repo/semantics/article