本研究目的是針對時間數列模式與模糊時間數列之二因子模式、引導式模式及馬可夫模式預測方法在應用上之比較，同時探討模糊時間數列模式在不同等份下，其預測誤差之變化，並以臺灣出口金額之預測為例。由本文實証結果發現，模糊時間數列模式在研究期間較短時有較佳的預測能力，其中以引導式模式之操作方法最為簡易，預測結果相對較佳，時間數列ARIMA模式在較長的研究期間其預測誤差（MSE）較小。而模糊時間數列模式最適區間長度的選取並非組距愈小愈好，最適區間長度會因模式不同而有所差異。

The study compares the application of the forecasting methods of ARIMA time series and fuzzy time series by Two-factor models, Heuristic models, and Markov models on the amount of Taiwan export. The study compares the forecasting results of different interval length by the three models of fuzzy time series From the conclusion, we find that the methods of fuzzy time series models have better forecasting ability than ARIMA time series model for a short period, namely their mean square error (MSE) is smaller. The Heuristic model is the easiest method to follow. The results suggested that the smaller the interval length is not always the better, and the effective length of interval differed from models.