Research on the prediction model of grain yield based on the ARIMA method
- 10.2991/icsmim-15.2016.84How to use a DOI?
- grain yield, forecasting, ARIMA model, prediction error
In order to predict the grain yield of the country accurately, considering the periodical fluctuation of the data, the method of time series is used. Firstly, the stability and the relativity of the yield series from year 1980 to 2009 are analyzed, and the first-order difference of which is calculated to get a stationary series. Then, after comparing the value of AIC of different models, the forecasting model ARIMA(5,1,5) is selected as the best one, and the performance of which is tested. Lastly, the grain yields from year 2010 to 2012 are predicted by three different methods, the results shown that, the prediction error of the model ARIMA(5,1,5) is 4.478%, the error of the grey model GM(1,1) is 6.78%, and the error of the second exponential smoothing method is 7.682%, thus, the model ARIMA(5,1,5) is more suitable to forecast the grain yield in short-term.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Chao Fan AU - Pei-Ge Cao AU - Tie-Jun Yang AU - Hong-Liang Fu PY - 2016/01 DA - 2016/01 TI - Research on the prediction model of grain yield based on the ARIMA method BT - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials PB - Atlantis Press SP - 454 EP - 458 SN - 2352-538X UR - https://doi.org/10.2991/icsmim-15.2016.84 DO - 10.2991/icsmim-15.2016.84 ID - Fan2016/01 ER -