Applying Grey Prediction, ANN, ARIMA and SARIMA to Forecast Taiwan’s Outflow Visitors
Date Issued
2007
Date
2007
Author(s)
Chen, I-Chih
Abstract
In earlier studies, grey prediction has been broadly used in different fields. Most of them applied annual data to construct forecasting model. If we use quarterly or monthly data to forecast, the results may be more useful and meaningful. This research amends grey prediction and uses it to forecast. In order to make sure the amended method works well, we then compare the results of the amended grey prediction with other forecasting methods. n this research, we apply grey prediction, ANN, ARIMA and SARIMA to forecast the quarterly and monthly numbers of people going abroad to Hong Kong, Japan, Korea, Thailand and Asia. We found that the performance of amended grey prediction is as good as SARIMA model, which is the best forecasting method in earlier papers. Because of the characters of easy-handled and requiring less data series, the amended grey prediction can also work well in some condition that SARIMA model can’t do.
Subjects
grey prediction
outflow visitor
Type
thesis
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