ARIMA and ARIMA-ERNN models for prediction of pertussis incidence in mainland China from 2004 to 2021

ARIMA and ARIMA-ERNN models for prediction of pertussis incidence in mainland China from 2004 to 2021

Abstract Objective To compare an autoregressive integrated moving average (ARIMA) model with a model that combines ARIMA with the Elman recurrent neural network (ARIMA-ERNN) in predicting the incidence of pertussis in mainland China. Background The incidence of pertussis has increased rapidly in mai...

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Bibliographic Details
Main Authors: Meng Wang, Jinhua Pan, Xinghui Li, Mengying Li, Zhixi Liu, Qi Zhao, Linyun Luo, Haiping Chen, Sirui Chen, Feng Jiang, Liping Zhang, Weibing Wang, Ying Wang
Format: Article
Language:English
Published: BMC 2022-07-01
Series:BMC Public Health
Subjects:
Pertussis
ARIMA model
ARIMA-ERNN model
Predictive effect
Online Access:https://doi.org/10.1186/s12889-022-13872-9

Internet

https://doi.org/10.1186/s12889-022-13872-9

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