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A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China
In recent years, the incidence of hepatitis B (HB) in Guangxi is higher than that of the national level; it has been increasing, so it is urgent to do a good predictive research of HB incidence, which can help analyze the early warning of hepatitis B in Guangxi, China. In the study, the feasibility...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314421/ https://www.ncbi.nlm.nih.gov/pubmed/32579598 http://dx.doi.org/10.1371/journal.pone.0234660 |
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author | Zheng, Yanling Zhang, Liping Zhu, XiXun Guo, Gang |
author_facet | Zheng, Yanling Zhang, Liping Zhu, XiXun Guo, Gang |
author_sort | Zheng, Yanling |
collection | PubMed |
description | In recent years, the incidence of hepatitis B (HB) in Guangxi is higher than that of the national level; it has been increasing, so it is urgent to do a good predictive research of HB incidence, which can help analyze the early warning of hepatitis B in Guangxi, China. In the study, the feasibility of predicting HB incidence in Guangxi by autoregressive integrated moving average (ARIMA) model method and Elman neural network (ElmanNN) method was discussed respectively, and the prediction accuracy of the two models was compared. Finally, we established the ARIMA (0, 1, 1) model and ElmanNN with 8 neurons. Both ARIMA (0, 1, 1) model and ElmanNN model had good performance, and their prediction accuracy were high. The fitting and prediction root-mean-square error (RMSE) and mean absolute error (MAE) of ElmanNN were smaller than those of ARIMA (0, 1, 1) model, which indicated that ElmanNN was superior to ARIMA (0, 1, 1) model in predicting the incidence of hepatitis B in Guangxi. Based on the ElmanNN, the HB incidence from September 2019 to December 2020 in Guangxi was predicted, the predicted results showed that the incidence of HB in 2020 was slightly higher than that in 2019 and the change trend was similar to that in 2019, for 2021 and beyond, the ElmanNN model could be used to continue the predictive analysis. |
format | Online Article Text |
id | pubmed-7314421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73144212020-06-29 A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China Zheng, Yanling Zhang, Liping Zhu, XiXun Guo, Gang PLoS One Research Article In recent years, the incidence of hepatitis B (HB) in Guangxi is higher than that of the national level; it has been increasing, so it is urgent to do a good predictive research of HB incidence, which can help analyze the early warning of hepatitis B in Guangxi, China. In the study, the feasibility of predicting HB incidence in Guangxi by autoregressive integrated moving average (ARIMA) model method and Elman neural network (ElmanNN) method was discussed respectively, and the prediction accuracy of the two models was compared. Finally, we established the ARIMA (0, 1, 1) model and ElmanNN with 8 neurons. Both ARIMA (0, 1, 1) model and ElmanNN model had good performance, and their prediction accuracy were high. The fitting and prediction root-mean-square error (RMSE) and mean absolute error (MAE) of ElmanNN were smaller than those of ARIMA (0, 1, 1) model, which indicated that ElmanNN was superior to ARIMA (0, 1, 1) model in predicting the incidence of hepatitis B in Guangxi. Based on the ElmanNN, the HB incidence from September 2019 to December 2020 in Guangxi was predicted, the predicted results showed that the incidence of HB in 2020 was slightly higher than that in 2019 and the change trend was similar to that in 2019, for 2021 and beyond, the ElmanNN model could be used to continue the predictive analysis. Public Library of Science 2020-06-24 /pmc/articles/PMC7314421/ /pubmed/32579598 http://dx.doi.org/10.1371/journal.pone.0234660 Text en © 2020 Zheng et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Zheng, Yanling Zhang, Liping Zhu, XiXun Guo, Gang A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China |
title | A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China |
title_full | A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China |
title_fullStr | A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China |
title_full_unstemmed | A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China |
title_short | A comparative study of two methods to predict the incidence of hepatitis B in Guangxi, China |
title_sort | comparative study of two methods to predict the incidence of hepatitis b in guangxi, china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314421/ https://www.ncbi.nlm.nih.gov/pubmed/32579598 http://dx.doi.org/10.1371/journal.pone.0234660 |
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