The tourism demand forecasting using a novel high-precision fuzzy time series model for the Japanese to Taiwan

• Main Authors: Ting-Chun Kuo, 郭亭君
• Other Authors: Ruey_Chyn Tsaur
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/49309800833291878570

碩士 === 淡江大學 === 管理科學研究所碩士班 === 98 === Over the past few decades, the tourism industry has been grown very fast. Because of the tourism activity may for the country creation traveling income, plan and the management sightseeing resources because of the forecasting result. Thus, it is very important for planning for potential tourism demand and improving the tourism infrastructure, since accurate forecasting of tourist arrivals. Japan has been the most important source that Taiwan travels all the time. But the international exchange is frequent day by day, the competition of the tour undertaking is fiercer and fiercer, only depend on correct decision and planning and management of perfection. There are many method can forecast, but when the collected are not enough to model regression model or time series model, or there exist fuzzy time series data, the statistical quantitative methods are usually failure to have smaller forecasting error. In order to provide a much more flexible examination for managing smaller data set or fuzzy data. In this study, we proposed an adaptive fuzzy time series model for forecasting tourism demand for Japanese to Taiwan. But it can’t forecast accurately, and it can’t forecast about untrained data, so we proposed a new method which combined Fourier series with fuzzy time series for forecasting Japanese tourism demand for Taiwan, and obtained very small forecasting error MAPE and RMSE.