Application of the GRA and SVM for Forecast of China Grain Production

Abstract:

This paper proposes a new method: GRA-SVM model which is composed of GRA and SVM to predict grain production through annual production data. In view of the fact that the complexity and incomplete information of grain production system, the primary factors influencing the grain production is decided on the basis of the grey ralational analysis of the grain producing system, then, the grey ralational analysis and support vector machine model is established by the principle of the support vection machine regression. The application case proved that the proposed method can improve the feasibility of the program in grain production, and it is suitable for on-line grain production control for food system.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 1106-1111
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.1106
• Online since: January 2012
• Authors: Jin Fa Shi, He Jun Jiao
• Keywords: Forecast of Grain Production, Grey Relational Analysis (GRA), Statistical Learning Theory, Support Vector Machine (SVM)

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