ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19

As a large agricultural country, China’s vegetable prices affect the increase in production and income of farmers and the daily life of urban and rural residents and influence the healthy development of Chinese agriculture. 51,567 vegetable price data of 2020 are analyzed to determine the factors th...

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Detalles Bibliográficos
Autores principales: Mao, Lisha, Huang, Yin, Zhang, Xiaofan, Li, Sijin, Huang, Xiangni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333317/
https://www.ncbi.nlm.nih.gov/pubmed/35901077
http://dx.doi.org/10.1371/journal.pone.0271594
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author Mao, Lisha
Huang, Yin
Zhang, Xiaofan
Li, Sijin
Huang, Xiangni
author_facet Mao, Lisha
Huang, Yin
Zhang, Xiaofan
Li, Sijin
Huang, Xiangni
author_sort Mao, Lisha
collection PubMed
description As a large agricultural country, China’s vegetable prices affect the increase in production and income of farmers and the daily life of urban and rural residents and influence the healthy development of Chinese agriculture. 51,567 vegetable price data of 2020 are analyzed to determine the factors that influence vegetable price fluctuations in two dimensions (vertical and horizontal) in the special context of the COVID-19, and an ARIMA model of short-term price prediction is then employed and evaluated. Based on the factors affecting vegetable prices, the results of the model are further examined. Finally, pertinent suggestions are made for the development of the local vegetable industry in the post-epidemic era.
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spelling pubmed-93333172022-07-29 ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19 Mao, Lisha Huang, Yin Zhang, Xiaofan Li, Sijin Huang, Xiangni PLoS One Research Article As a large agricultural country, China’s vegetable prices affect the increase in production and income of farmers and the daily life of urban and rural residents and influence the healthy development of Chinese agriculture. 51,567 vegetable price data of 2020 are analyzed to determine the factors that influence vegetable price fluctuations in two dimensions (vertical and horizontal) in the special context of the COVID-19, and an ARIMA model of short-term price prediction is then employed and evaluated. Based on the factors affecting vegetable prices, the results of the model are further examined. Finally, pertinent suggestions are made for the development of the local vegetable industry in the post-epidemic era. Public Library of Science 2022-07-28 /pmc/articles/PMC9333317/ /pubmed/35901077 http://dx.doi.org/10.1371/journal.pone.0271594 Text en © 2022 Mao et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mao, Lisha
Huang, Yin
Zhang, Xiaofan
Li, Sijin
Huang, Xiangni
ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19
title ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19
title_full ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19
title_fullStr ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19
title_full_unstemmed ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19
title_short ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19
title_sort arima model forecasting analysis of the prices of multiple vegetables under the impact of the covid-19
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333317/
https://www.ncbi.nlm.nih.gov/pubmed/35901077
http://dx.doi.org/10.1371/journal.pone.0271594
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