Cargando…
Medical service demand forecasting using a hybrid model based on ARIMA and self-adaptive filtering method
BACKGROUND: Accurate forecasting of medical service demand is beneficial for the reasonable healthcare resource planning and allocation. The daily outpatient volume is characterized by randomness, periodicity and trend, and the time series methods, like ARIMA are often used for short-term outpatient...
Autores principales: | Huang, Yihuai, Xu, Chao, Ji, Mengzhong, Xiang, Wei, He, Da |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501710/ https://www.ncbi.nlm.nih.gov/pubmed/32950059 http://dx.doi.org/10.1186/s12911-020-01256-1 |
Ejemplares similares
-
Comparison of ARIMA, ES, GRNN and ARIMA–GRNN hybrid models to forecast the second wave of COVID-19 in India and the United States
por: Wang, Gang, et al.
Publicado: (2021) -
Application of ARIMA, and hybrid ARIMA Models in predicting and forecasting tuberculosis incidences among children in Homa Bay and Turkana Counties, Kenya
por: Siamba, Stephen, et al.
Publicado: (2023) -
Forecasting daily Covid-19 cases in the world with a hybrid ARIMA and neural network model
por: de Araújo Morais, Lucas Rabelo, et al.
Publicado: (2022) -
Forecasting Covid-19 Transmission with ARIMA and LSTM Techniques in Morocco
por: Rguibi, Mohamed Amine, et al.
Publicado: (2022) -
A Hybrid Neural Network Model for Sales Forecasting Based on ARIMA and Search Popularity of Article Titles
por: Omar, Hani, et al.
Publicado: (2016)