Forecasting Taiwan’s Tourism Demand by Fuzzy Time Series
碩士 === 逢甲大學 === 國際貿易所 === 95 === The purpose of this paper is to apply the neural networks to implement a new fuzzy time series model to forecast the tourism demand in Taiwan. The neural networks are used to compute the degrees of memberships and then fuzzy relationships. The fuzzy relationships are...
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| Format: | Others |
| Language: | en_US |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/56410716265718788456 |
| Summary: | 碩士 === 逢甲大學 === 國際貿易所 === 95 === The purpose of this paper is to apply the neural networks to implement a new fuzzy time series model to forecast the tourism demand in Taiwan. The neural networks are used to compute the degrees of memberships and then fuzzy relationships. The fuzzy relationships are then used to forecast the tourist numbers arriving Taiwan. At first, we apply this way to estimate enrollments of the university in Alabama adopted from Song and Chissom (1993) and compare the result with Song and Chissom (1993) and Chen (1996). The result is better than theirs. Then, Both estimation and forecasting are conducted in Taiwan’s tourism demand. The results of the estimation are used to determine the threshold for forecasting. The forecasting results are shown to outperform those of the previous studies.
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