Wastewater flow forecasting model based on the nonlinear autoregressive with exogenous inputs (NARX) neural network
Wastewater flow forecasts are key components in the short- and long-term management of sewer systems. Forecasting flows in sewer networks constitutes a considerable uncertainty for operators due to the nonlinear relationship between causal variables and wastewater flows. This work aimed to fill the...
Guardado en:
Autores principales: | Khalid El Ghazouli, Jamal El Khattabi, Isam Shahrour, Aziz Soulhi |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IWA Publishing
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/acaba128efb44022aa99f9859b5b0891 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Nonlinear Autoregressive Model With Exogenous Input Recurrent Neural Network to Predict Satellites’ Clock Bias
por: Yifeng Liang, et al.
Publicado: (2021) -
Artificial neural network modeling approach for the prediction of five-day biological oxygen demand and wastewater treatment plant performance
por: Abdalrahman Alsulaili, et al.
Publicado: (2021) -
Historical evolution of urban water conservancy projects in Xi'an, China in the past 3,000 years and its revelations
por: Wei Zhou, et al.
Publicado: (2021) -
A Modular Tide Level Prediction Method Based on a NARX Neural Network
por: Wenhao Wu, et al.
Publicado: (2021) -
Flood forecasting using an improved NARX network based on wavelet analysis coupled with uncertainty analysis by Monte Carlo simulations: a case study of Taihu Basin, China
por: Feiqing Jiang, et al.
Publicado: (2021)