Agricultural Yields Forecasting by Time Series Methods

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Norawat Luangtong
Nantachai Kantanantha


This research’s objective is to study the forecasting methods for the agricultural yields of four crops including in-season rice, off-season rice, cassava and pineapple in the provinces with the three highest yields of Thailand. Then the appropriate forecasting methods are selected by comparing the forecasting results from four time series methods including simple exponential smoothing, double exponential smoothing, additive Holt-Winters and multiplicative Holt-Winters. The forecast accuracy is compared by mean absolute percentage error (MAPE). The results of the study showed that the MAPEs of in-season rice ranged from 6.74 to 12.59 percent, the MAPEs of off-season rice ranged from 4.65 to 15.27 percent, the MAPEs of cassava ranged from 7.28 to 15.10 percent and the MAPEs of pineapple ranged from 8.45 to 14.89 percent. The appropriate forecasting methods for each crop of the studied provinces are concluded as Table 7 in the article.

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How to Cite
Luangtong, N., & Kantanantha, N. (2015). Agricultural Yields Forecasting by Time Series Methods. Thai Industrial Engineering Network Journal, 1(1), 7–13. Retrieved from
Research and Review Article


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