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Short‐term forecast of pig price index on an agricultural internet platform

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  • Ming Wang

Abstract

From the perspective of agribusiness, the market price of live pigs reflects the current demand. Therefore, tracking and forecasting market prices are important tasks in agrimanagement, by which the production schedule can be adjusted to increase profit. An agricultural internet platform was developed as an integrated cloud service for market tracking. To quantitatively forecast online pig trading, in this study, a short‐term forecasting model of the pig price index was developed; the model automatically retrieved historical data as a training data set and determined the price index forecast with an autoregressive integrated moving average (ARIMA) algorithm for a time‐series analysis. The mean square error (MSE) of the AR(1) model for predicting the pig price index in Henan Province was 159.010, and the MSE of the ARIMA(1,1) model for predicting pig price index in Fujian Province was 92.294. The results demonstrated that the error between the predicted calculation and verification test results was small, and the results efficiently improved the prediction accuracy (EconLit citations: C6, L86, Q1).

Suggested Citation

  • Ming Wang, 2019. "Short‐term forecast of pig price index on an agricultural internet platform," Agribusiness, John Wiley & Sons, Ltd., vol. 35(3), pages 492-497, July.
    • Handle: RePEc:wly:agribz:v:35:y:2019:i:3:p:492-497
    DOI: 10.1002/agr.21607
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    References listed on IDEAS

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    1. Somwaru, Agapi & Zhang, Xiaohui & Tuan, Francis C., 2003. "China'S Hog Production Structure And Efficiency," 2003 Annual meeting, July 27-30, Montreal, Canada 22003, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Verdouw, Cor N. & Vucic, Nicola & Sundmaeker, Harald & Beulens, Adriaan J.M., 2014. "Future Internet as a Driver for Virtualization, Connectivity and Intelligence of Agri-Food Supply Chain Networks," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 4(4), pages 1-12, February.
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