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Grain Ration Consumption Forecasting based on Multivariate Regression Model Combined with Gliding Data Barycenter

Volume 14, Number 8, August 2018, pp. 1666-1673
DOI: 10.23940/ijpe.18.08.p2.16661673

Chunhua Zhu and Jiaojiao Wang

College of Information Science and Engineering, Henan University of Technology, Zhengzhou, 450001, China

(Submitted on May 9, 2018; Revised on June 16, 2018; Accepted on July 19, 2018)


To address the existing and limited original data and lower prediction robustness, a new multivariate regression forecasting model combined with gliding data barycenter was proposed. In this new forecasting method, the original data was interpolated and the corresponding data barycenter was optimized. Then, the important impact factors of ration consumption were analysed and chosen for the multivariate regression model. In simulation experiments, the training data of 35 years (1981-2015) were used, and the results have shown that the proposed method can greatly improve prediction accuracy and robustness.


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