Prediction of permeate flux decline in crossflow membrane filtration of colloidal suspension: a radial basis function neural network approach
- 10 May 2006
- journal article
- Published by Elsevier BV in Desalination
- Vol. 192 (1-3), 415-428
- https://doi.org/10.1016/j.desal.2005.07.045
Abstract
No abstract availableThis publication has 29 references indexed in Scilit:
- Input determination for neural network models in water resources applications. Part 1—background and methodologyJournal of Hydrology, 2005
- Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a riverJournal of Hydrology, 2005
- Artificial neural network technique for rainfall forecasting applied to the São Paulo regionJournal of Hydrology, 2004
- Non-invasive measurement of membrane morphology via UFDR: pore-size characterizationJournal of Membrane Science, 2004
- Cake Structure in Dead-End Membrane Filtration: Monte Carlo SimulationsEnvironmental Engineering Science, 2002
- Use of neural networks for predictions using time series: Illustration with the El Niño Southern oscillation phenomenonNeurocomputing, 2000
- Dynamic ultrafiltration of proteins – A neural network approachJournal of Membrane Science, 1998
- Flux decline in crossflow microfiltration and ultrafiltration: mechanisms and modeling of membrane foulingJournal of Membrane Science, 1998
- Simulation of membrane separation by neural networksJournal of Membrane Science, 1995
- Theoretical descriptions of membrane filtration of colloids and fine particles: An assessment and reviewAdvances in Colloid and Interface Science, 1995