Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials

Research on the prediction model of grain yield based on the ARIMA method

Authors
Chao Fan, Pei-Ge Cao, Tie-Jun Yang, Hong-Liang Fu
Corresponding Author
Chao Fan
Available Online January 2016.
DOI
https://doi.org/10.2991/icsmim-15.2016.84How to use a DOI?
Keywords
grain yield, forecasting, ARIMA model, prediction error
Abstract

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.

Copyright
© 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/).

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Volume Title
Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
Series
Advances in Computer Science Research
Publication Date
January 2016
ISBN
978-94-6252-157-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icsmim-15.2016.84How to use a DOI?
Copyright
© 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  - https://doi.org/10.2991/icsmim-15.2016.84
ID  - Fan2016/01
ER  -