Study on the Effect of COVID-19 on Agricultural Industrialization Based on Big Data of Electrical Power

Xiang Fang, Yi Wang, Lin Xia, Yi Xuan, Xianghai Xu, Zhiqing Sun, Junhai Wang
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Abstract

Under the wake of COVID-19, agricultural production and people's consumption are seriously affected, in addition, the number of methods to quantitatively analyze of the degree of influence is limited. The big data of electrical power can accurately reflect the business situation of enterprises in the industry. This paper select hundreds of leading enterprises in agricultural industrialization as the analysis objects, and use Keyword Index Technology to construct the corresponding system of enterprise name-electric household number, and use Multilevel Coordination Algorithm to fit the electricity curve of leading enterprises in agricultural industrialization, to study the impact degree difference and resilience of the epidemic situation on the subdivision industry, and use Covariance Analysis Algorithm to analyze the correlation of subdivision industry under the epidemic situation, and to give the prospect of development opportunities in the period after the COVID-19 epidemic situation.
基于电力大数据的新冠肺炎疫情对农业产业化的影响研究
新冠肺炎疫情后,农业生产和居民消费受到严重影响,定量分析影响程度的方法有限。电力大数据可以准确反映行业内企业的经营状况。本文选取数百家农业产业化龙头企业作为分析对象,运用关键词指标技术构建相应的企业名称-用电户数体系,运用多层次协调算法拟合农业产业化龙头企业的用电曲线,研究疫情对细分行业的影响程度差异和弹性。并运用协方差分析算法对疫情下细分行业的相关性进行分析,给出疫情后一段时期的发展机遇前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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