A comparison study between fuzzy time series model and ARIMA model for forecasting Taiwan export

作者：Wang Chi Chen^*

来源：Expert Systems with Applications, 2011, 38(8): 9296-9304.

DOI：10.1016/j.eswa.2011.01.015

• ARIMA model
• Fuzzy time series
• Taiwan export

This study compares the application of two forecasting methods on the amount of Taiwan export, the ARIMA time series method and the fuzzy time series method. Models discussed for the fuzzy time series method include the Factor models, the Heuristic models, and the Markov model. When the sample period is prolong in our models, the ARIMA model shows smaller than predicted error and closer predicted trajectory to the realistic trend than those of the fuzzy model, resulted in more accurate forecasts of the export amount in the ARIMA model. Especially, the coefficient of the en-or term for the previous period has increased to 79%, implying the influential effect of external factors. These external factors attribute to the export amount of Taiwan according to the economic viewpoints. However, this impact reduces as time progressing and the export amount of the lag period of 12 or 13 do not affect current export amount any-more. In conclusion. when the sample period is shorter with only a small set of data available, the fuzzy time series models can be utilized to predict export values accurately, outperforming the ARIMA model.

• 出版日期2011-8
• 单位中国人民解放军国防大学