Cargando…
Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization
Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empiric...
Autores principales: | Huang, Daizheng, Wu, Zhihui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319685/ https://www.ncbi.nlm.nih.gov/pubmed/28222194 http://dx.doi.org/10.1371/journal.pone.0172539 |
Ejemplares similares
-
Application of a Hybrid Method Combining Grey Model and Back Propagation Artificial Neural Networks to Forecast Hepatitis B in China
por: Gan, Ruijing, et al.
Publicado: (2015) -
An Empirical Mode Decomposition Fuzzy Forecast Model for COVID-19
por: Chen, Bo-Lun, et al.
Publicado: (2022) -
An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality
por: Jiang, Wenxin, et al.
Publicado: (2022) -
Empirical mode decomposition using deep learning model for financial market forecasting
por: Jin, Zebin, et al.
Publicado: (2022) -
A hybrid model for tuberculosis forecasting based on empirical mode decomposition in China
por: Zhao, Ruiqing, et al.
Publicado: (2023)