Dynamic ultrafiltration modelling for a submerged membrane bioreactor based on neural networks

Abstract:

A neural network (NN) model to pbkp_redict the membrane performance in a scale pilot submerged membrane bioreactor (SMBR) has been developed. This SMBR has been used for the aerobic treatment of municipal wastewater. The aim of this work was to pbkp_redict the dynamic behavior of the transmembrane pressure (TMP) as a function of three operating parameters, i.e., permeate flux, the mixed liquor suspended solids and the hydraulic cleaning cycles. The applied NN was a multilayer perceptron network (MLPN) and the Levenberg-Marquardt (LM) optimization algorithm was employed for its training. © 2010 Taylor & Francis Group, London.

Año de publicación:

2010

Keywords:

• Neural networks
• Membrane bioreactor
• Ultrafiltration

Fuente:

scopus