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甘肃省猪肉价格预测与风险预警研究OA

Pork Price Forecasting and Risk Early Warning in Gansu Province

中文摘要英文摘要

对猪肉价格进行预测、预警,可以有效指导生猪养殖,保障猪肉供需平衡.为促进甘肃省猪肉市场稳定可持续发展,本研究以猪肉价格为研究对象,运用Lasso算法筛选变量,利用哈里斯鹰优化算法(HHO)对随机森林(RF)进行改进,建立预测模型HHO-RF,对猪肉价格进行预测、预警.结果表明:HHO-RF模型均方误差(MSE)为 0.22,可决系数(R2)为 99.76%,相对分析误差(PRD)为 20.6,具有较好的拟合效果;对猪肉价格的风险预警效果较好,准确率达到91.67%,说明模型HHO-RF可以较为准确地预测甘肃省猪肉价格走势.对 2022 年11月至 2025 年10月甘肃省猪肉价格预测发现,预测期内价格整体呈现先降后升最后稳定的趋势.基于此,推动甘肃省猪肉产业健康发展,建议优化猪肉价格预测系统,提高价格预测精度;拓宽猪肉价格信息公布通道,促进信息共享;建立健全猪肉价格风险预警体系,提高应急调控水平.

The forecast and early warning of pork price can effectively guide pig breeding and ensure the supply and demand balance.In order to promote the stable and sustainable development of the pork market in Gansu province,the authors used the pork price as the research object,screened the variables by using the Lasso regression,improved the random forest by using the HHO,and the HHO-RF was established to forecast and early-warning.The results showed that the MSE is 0.22,the R2 is 99.76%,and the PRD is 20.6,which has a good fitting effect;the risk early warning effect of pork price is good,and the accuracy rate reaches 91.67%,which showes that the model HHO-RF can accurately predict the price of pork in Gansu province.The forecast for the pork price in Gansu province from November 2022 to October 2025 showed that the overall trend of prices during the forecast period is first falling,then rising and finally stabilizing.Based on this,some suggestions on the healthy development of pork industry in Gansu province were put forward from optimizing the pork price forecasting system to improve the precision of price forecasting,expanding the channel of pork price information announcement to promote the information sharing,and establishing and improving the pork price risk early warning system to improve the level of emergency regulation.

周玉兰;李爱爱;王官娟

西北师范大学数学与统计学院 甘肃 兰州 730070

猪肉价格走势预测Lasso回归随机森林哈里斯鹰优化算法风险预警机制

pork pricetrend forecastLasso regressionRandom ForestHarris's Hawk optimization algorithmrisk warning mechanism

《农业展望》 2024 (004)

11-18 / 8

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