Abstract
Fully connected multi-layer feedforward artificial neural networks trained using the error-back-propagation algorithm have been employed to identify the nonlinear multi-variable, multi-stage flash (MSF) desalination plant. Both multiple input-single output (MISO) and multiple input-multiple output (MIMO) networks have been used for the purpose of identification. The correlation coefficient values greater than 0.99 were obtained suggesting that the neural network can serve as a good alternative to a model MSF desalination plant.
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