Research on Intelligent Decision Method Based on Grey System Theory in the Prediction of Grain Yield in Jilin Province

Abstract:

In order to improve the prediction ability of grain yield, the grain yield data of Jilin province is taken as the research object, GM(1,1) model and GM (1,N) model is established. According to the correlation analysis results, some key correlation factors of grain yield are selected into the prediction model, including the amount of chemical fertilizer, the end head of livestock, the grain sown area etc, and carries on the forecast to the grain yield of 2010-2012. The predicted results show that the average prediction error of GM(1,1) model is 6.6705% and the average prediction error of GM (1,N) model is 5.2020%. Through the comparative analysis, GM (1,N) model has higher prediction accuracy for the multiple attribute intelligent decision problem, it can be used for the prediction of grain yield in Jilin province.

• Periodical: Applied Mechanics and Materials (Volumes 519-520)
• Pages: 775-779
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.519-520.775
• Online since: February 2014
• Authors: Xing Mei Xu*
• Keywords: Gm (1,N) Model, GM(1,1) Model, Intelligent Decision, Production Prediction

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