非洲猪瘟影响猪肉价格动态的大数据分析实验设计

Experimental design of big data analysis of pork price dynamics affected by African Swine Fever

该文设计了非洲猪瘟影响猪肉价格动态的大数据分析综合数学实验项目。首先运用网络爬虫和文本挖掘技术建立了非洲猪瘟舆情语料库,综合运用LDA主题模型、机器学习情感分类算法和TF-IDF权重算法构建了非洲猪瘟舆情指数,建立了猪肉价格与舆情指数的VAR模型,并对其进行了Grange因果关系检验、脉冲响应分析和方差分解分析。结果表明,非洲猪瘟疫情对猪肉价格存在冲击和影响,是猪肉价格波动的Grange原因,且不同时期对猪肉价格的冲击大小存在差异。该实验设计涵盖了文本大数据的挖掘技术、Python编程、VAR模型的构建与解释、动物疫情、生猪养殖和农业经济学等,有益于提高学生在大数据环境下综合运用多种分析工具和统计知识解决实际问题的能力。

A comprehensive mathematical experiment project on big data analysis of pork price dynamics affected by African Swine Fever has been designed.Firstly,a corpus of public opinion on African Swine Fever has been established by using a web crawler and text mining techniques,an African Swine Fever public opinion index has been constructed by integrating an LDA topic model,machine learning sentiment classification algorithm,and TF-IDF weighting algorithm,a VAR model of pork price and public opinion index has been established,and Grange causality test,impulse response analysis,and variance decomposition analysis have been conducted.The results show that there is an impact and influence of the African Swine Fever epidemic on pork price,which is the Grange cause of pork price fluctuation,and there is a difference in the size of the impact on pork price in different periods.The experimental design covers the mining techniques of textual big data,Python programming,construction and interpretation of VAR models,animal epidemic,pig breeding,agricultural economics,etc.It is beneficial to improve students’ability to synthesize multiple analytical tools and statistical knowledge to solve practical problems in a big data environment.