Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans

Background: We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schisto...

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Detalles Bibliográficos
Autores principales: Zhou, Lingling, Xia, Jing, Yu, Lijing, Wang, Ying, Shi, Yun, Cai, Shunxiang, Nie, Shaofa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4847017/
https://www.ncbi.nlm.nih.gov/pubmed/27023573
http://dx.doi.org/10.3390/ijerph13040355

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4847017/
https://www.ncbi.nlm.nih.gov/pubmed/27023573
http://dx.doi.org/10.3390/ijerph13040355

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