Abstract
Neural networks have been successfully applied as intelligent sensors for process modeling and control. In this paper, the application of soft sensors in the cane sugar industry is discussed. A neural network is trained on historical data to predict process quality variables so that it can replace the lab-test procedure. An immediate benefit of building intelligent sensors is that the neural network can predict product quality in a timely manner.
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