农业大数据学报 ›› 2023, Vol. 5 ›› Issue (1): 126-134.doi: 10.19788/j.issn.2096-6369.230121

• 研究论文 • 上一篇    

大数据技术在猪肉价格预测与调控上的探索与应用

金语泽1(), 贾昕为2, 赖望峰1, 周宏立1, 陈乃赫1, 李涛2,*()   

  1. 1.神州数码信息系统有限公司,北京 100080
    2.农业农村部信息中心,北京 100125
  • 收稿日期:2022-07-05 出版日期:2023-03-26 发布日期:2023-05-16
  • 通讯作者: 李涛,男,高级工程师,研究方向:农业信息化;E-mail: litao@agri.gov.cn
  • 作者简介:金语泽,女,硕士,工程师,研究方向:人工智能、数据挖掘; E-mail: jinyzd@dcits.com

Exploration and Application of Big Data Technology in Pork Price Prediction and Regulation

JIN Yuze1(), JIA Xinwei2, LAI Wangfeng1, ZHOU Hongli1, CHEN Naihe1, LI Tao2,*()   

  1. 1. Digital China Information Service Company Ltd., Beijing 100080, China
    2. Information Center, Ministry of Agriculture and Rural Affairs, Beijing 100125, China
  • Received:2022-07-05 Online:2023-03-26 Published:2023-05-16

摘要:

我国是生猪养殖大国,也是猪肉消费大国。猪肉价格波动直接影响养猪户利益,也会对居民生活产生影响。预测未来猪肉价格走势,科学管控生猪市场价格,对推进我国生猪市场平稳健康运行具有重要现实意义。本文以全国生猪出场价格为研究对象,首先根据生猪生产的生物周期和生产的连续性特点,构建生猪出栏量、能繁母猪存栏量与猪肉产量三者之间的关系模型,预测出未来10个月的猪肉产量。再结合我国受猪肉消费习惯影响,致使猪肉需求量呈现明显季节性周期波动的特点,采用STL时间序列分解法,从猪肉交易数据中提炼出月度季节性波动趋势,预测月度猪肉需求量。基于定价模型中供需法则,使用最小二乘法约束法,构建猪肉供应量和需求量比与猪肉价格之间的关系模型,对未来10个月猪肉价格进行预测,并测算出猪肉供需均衡价格。本研究使用农业农村部重点农产品市场信息平台系统中2016至2022年猪肉相关数据,预测猪肉价格相对误差约10%。当预测的猪肉供应量与需求量比出现偏离时,猪肉价格将偏离供需均衡价格,模型能够通过调控能繁母猪存栏量、进口量和投放量来调节猪肉供应量,从而调控未来猪肉价格走势。本研究提供了通过调整影响猪肉供应量的核心因素来调节未来猪肉价格走势的思路和方法,旨在科学预测猪肉供需量及未来价格走势,协助政府相关部门合理及时调控猪肉供给,促进各时刻的猪肉供需均衡,猪肉价格稳定在供需均衡的合理区间。

关键词: 供应量预测, 需求量预测, 供需均衡, 猪肉价格预测与调控

Abstract:

China is a country of large hog production and pork consumption. Fluctuations in pork prices directly affect the interests of hog farmers and residents' diets. Prediction of the future trend of pork prices and scientific control of pork prices plays an important and practical role in promoting the stable and healthy operation of hogs and pork industry of China. This article studies the national pork market price trend. Firstly, pork supply prediction model based on the number of live hog and breeding sows is built according to the biological cycle and continuity features of hog production, which can predict pork production in the next 10 months. Secondly, taking advantage of the obvious seasonal cycle fluctuations in pork demand caused by my country's pork consumption habits, the STL time series decomposition method is used to decompose the monthly seasonal fluctuation trend from the pork transaction data to predict the monthly pork demand. Thirdly, based on the law of supply and demand in the pricing model, the relationship model of the pork price and the ratio between pork supply and demand is constructed to predict pork price in the next 10 months and calculate the price of pork supply and demand equilibrium. The relative error of pork price prediction is about 10% by using pork-related data from the Agricultural Products Market Information Platform system of the Ministry of Agriculture and Rural Affairs in 2022. When the estimated future pork supply and demand deviates, the model can adjust the pork supply by regulating the number of breeding sows, the import volume and the delivery volume, thereby regulating the future pork price trend. This study provides ideas and methods to adjust future pork price trends by adjusting the core factors that affect pork supply. This study aims to assist relevant government departments in properly and timely regulation of pork supply on the basis of scientifically predicting pork supply and demand and future price trends, so as to balance the supply and demand of pork and maintain the price of pork within a reasonable range of balanced supply and demand.

Key words: Supply forecasting, Demand forecasting, Equilibrium of supply and demand, Pork price forecasting and regulation