Agricultural Yields Forecasting by Time Series Methods
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Abstract
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.
Article Details
บทความ ข้อมูล เนื้อหา รูปภาพ ฯลฯ ที่ได้รับการตีพิมพ์ในวารสารฯ ถือเป็นลิขสิทธิ์ของวารสารฯ หากบุคคลหรือหน่วยงานใดต้องการนำทั้งหมดหรือส่วนหนึ่งส่วนใดไปเผยแพร่ต่อหรือเพื่อกระทำการใดๆ จะได้รับอนุญาต แต่ห้ามนำไปใช้เพื่่อประโยชน์ทางธุรกิจ และห้ามดัดแปลง
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