Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.

<h4>Background</h4>In recent years, the price of pork in China continues to fluctuate at a high level. The forecast of pork price becomes more important. Single prediction models are often used for this work, but they are not accurate enough. This paper proposes a new method based on Cen...

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Autores principales:	Chuansheng Wang, Zhihua Sun
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f1f1ccfbb86f402ab6831ffa899d71f7
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spelling	oai:doaj.org-article:f1f1ccfbb86f402ab6831ffa899d71f72021-12-02T20:04:08ZMonthly pork price forecasting method based on Census X12-GM(1,1) combination model.1932-620310.1371/journal.pone.0251436https://doaj.org/article/f1f1ccfbb86f402ab6831ffa899d71f72021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0251436https://doaj.org/toc/1932-6203<h4>Background</h4>In recent years, the price of pork in China continues to fluctuate at a high level. The forecast of pork price becomes more important. Single prediction models are often used for this work, but they are not accurate enough. This paper proposes a new method based on Census X12-GM(1,1) combination model.<h4>Methods</h4>Monthly pork price data from January 2014 to December 2020 were obtained from the State Statistics Bureau(Mainland China). Census X12 model was adopted to get the long-term trend factor, business cycle change factor and seasonal factor of pork price data before September 2020. GM (1,1) model was used to fit and predict the long-term trend factor and business cycle change factor. The fitting and forecasting values of GM(1,1) were multiplied by the seasonal factor and empirical seasonal factor individually to obtain the fitting and forecasting values of the original monthly pork price series.<h4>Results</h4>The expression of GM(1,1) model for fitting and forecasting long-term trend factor and and business cycle change factor was X(1)(k) = -1704.80e-0.022(k-1) + 1742.36. Empirical seasonal factor of predicted values was 1.002 Using Census X12-GM(1,1) method, the final forecast values of pork price from July 2020 to December 2020 were 34.75, 33.98, 33.23, 32.50, 31.78 and 31.08 respectively. Compared with ARIMA, GM(1,1) and Holt-Winters models, Root mean square error (RMSE), mean absolute percentage error (MAPE) and mean absolute error (MAE) of Census X12-GM(1,1) method was the lowest on forecasting part.<h4>Conclusions</h4>Compared with other single model, Census X12-GM(1,1) method has better prediction accuracy for monthly pork price series. The monthly pork price predicted by Census X12-GM(1,1) method can be used as an important reference for stakeholders.Chuansheng WangZhihua SunPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0251436 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chuansheng Wang Zhihua Sun Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.
description	<h4>Background</h4>In recent years, the price of pork in China continues to fluctuate at a high level. The forecast of pork price becomes more important. Single prediction models are often used for this work, but they are not accurate enough. This paper proposes a new method based on Census X12-GM(1,1) combination model.<h4>Methods</h4>Monthly pork price data from January 2014 to December 2020 were obtained from the State Statistics Bureau(Mainland China). Census X12 model was adopted to get the long-term trend factor, business cycle change factor and seasonal factor of pork price data before September 2020. GM (1,1) model was used to fit and predict the long-term trend factor and business cycle change factor. The fitting and forecasting values of GM(1,1) were multiplied by the seasonal factor and empirical seasonal factor individually to obtain the fitting and forecasting values of the original monthly pork price series.<h4>Results</h4>The expression of GM(1,1) model for fitting and forecasting long-term trend factor and and business cycle change factor was X(1)(k) = -1704.80e-0.022(k-1) + 1742.36. Empirical seasonal factor of predicted values was 1.002 Using Census X12-GM(1,1) method, the final forecast values of pork price from July 2020 to December 2020 were 34.75, 33.98, 33.23, 32.50, 31.78 and 31.08 respectively. Compared with ARIMA, GM(1,1) and Holt-Winters models, Root mean square error (RMSE), mean absolute percentage error (MAPE) and mean absolute error (MAE) of Census X12-GM(1,1) method was the lowest on forecasting part.<h4>Conclusions</h4>Compared with other single model, Census X12-GM(1,1) method has better prediction accuracy for monthly pork price series. The monthly pork price predicted by Census X12-GM(1,1) method can be used as an important reference for stakeholders.
format	article
author	Chuansheng Wang Zhihua Sun
author_facet	Chuansheng Wang Zhihua Sun
author_sort	Chuansheng Wang
title	Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.
title_short	Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.
title_full	Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.
title_fullStr	Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.
title_full_unstemmed	Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.
title_sort	monthly pork price forecasting method based on census x12-gm(1,1) combination model.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/f1f1ccfbb86f402ab6831ffa899d71f7
work_keys_str_mv	AT chuanshengwang monthlyporkpriceforecastingmethodbasedoncensusx12gm11combinationmodel AT zhihuasun monthlyporkpriceforecastingmethodbasedoncensusx12gm11combinationmodel
_version_	1718375638012788736

Monthly pork price forecasting method based on Census X12-GM(1,1) combination model.

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