本研究針對國內國家級風景特定區之觀光遊客人數建立預測模型，利用Box-Jenkins四個步驟建立ARMA預測模型、ARIMA預測模型及利用迴歸分析進行實證研究，並以組合預測模式加以比較其預測績效。根據迴歸分析，本研究顯示消費者物價指數、國民所得、季節指數及上一期遊客人數、上一年之同期遊客人數對遊客參訪國家級風景特定區有影響。所得增加會增加民眾旅遊之意願，物價指數升高會影響旅遊之消費能力，季節指數顯示第三季高於第一、第二季，顯示第三季為臺灣國家級風景特定區之相對旺季；遊客明顯受到上一期之遊客人數影響，表示資訊傳播對民眾有正面影響。在預測績效的部分，本研究顯示由MAPE值、泰勒不等係數值、複判定係數與校正之複判定係數可看出預測組合確實能改善模型之精確度。

In this study, four steps from Box-Jenkins were used to set up ARMA model and ARIMA model, and the method of least squares regression was used to analyze and predict the number of visitors to national scenic areas, as well as show the performance of a combination of forecasting models. According to regression analysis, this study showed that CPI, GDP, seasonal indices, the number of tourists in the previous year, and the number of tourists in the same period in the previous year have a significant impact on the number of tourists to national scenic areas. Increase in income helped to increase people's willingness to travel, and price index helped to increase spending power during tourism seasons. The result of this study also indicated that the third quarter is relatively a peak season for Taiwan's national scenic areas and the dissemination of information had a positive impact on the number of tourists. In terms of forecast performance, results from the MAPE values, Taylor coefficients, R2 and adj R2, showed that accuracy can indeed improve through a combination of forecasting models.