乡村振兴背景下蔬菜价格波动因素分析及预测  

Vegetable Price Fluctuation Factors Analysis and Prediction under the Background of Rural Revitalization

作　　者：李忻怡 LI Xinyi(School of Statistics,Xi’an University of Finance and Economics,Xi’an 710100,China)

机构地区：[1]西安财经大学统计学院,西安710100

出　　处：《科技和产业》2023年第8期126-130,共5页Science Technology and Industry

基　　金：西安财经大学研究生创新基金一般项目(22YC014)。

摘　　要：近年来在农产品批发市场上,蔬菜价格波动幅度较大。将影响蔬菜价格的因素划分为供给、需求、流通、气候和其他5大类,构建Lasso-SVM最优组合预测模型预测蔬菜价格。研究结果表明:人民币汇率、新冠感染者月均增加人数、气温平均值、农业生产价格资料指数、农产品生产价格指数、劳动日工价、物质与服务费用、用工成本和蔬菜播种面积对蔬菜价格影响较大;对比多种预测模型发现,Lasso-SVM模型组合预测蔬菜价格准确度高、性能稳定。In recent years,vegetable prices have fluctuated greatly in the wholesale market of agricultural products.The factors affecting vegetable prices are divided into five categories,including supply,demand,circulation,climate and others,and the Lasso-SVM optimal combination prediction model is constructed to predict vegetable prices.The results show that the RMB exchange rate,the average monthly increase in the number of new crowns,the average temperature,the agricultural production price data index,the agricultural production price index,the daily labor price,the material and service costs,the labor cost and the vegetable sowing area have a great impact on the vegetable price.A variety of prediction models is compared,and it is found that the combination of Lasso-SVM model has high accuracy and stable performance in predicting vegetable prices.

关 键 词：乡村振兴 蔬菜价格波动 变量筛选 Lasso-SVM组合预测 

分 类 号：F323.7[经济管理—产业经济] F224