An Optimized Neural Network Model of Desalination by Vacuum Membrane Distillation Using Genetic Algorithm

An experimental based ANN model is constructed to describe the performance of vacuum membrane distillation process for desalination in different operating conditions. The vacuum pressure, the feed inlet temperature, the concentration of the feed salt aqueous solution and the feed flow rate are the input variables of this process, whereas the response is the permeate flux. The neural network approach was found to be capable for modeling this membrane distillation configuration. The application of Genetic Algorithm (GA) to optimize the ANN model parameters was also investigated.