September 1998

Special Report: Process Control and Information Systems

Applying neural networks

Use these practical guidelines for successful applications

Guiver, J., Neelakantan, R., Aspen Technology Inc.

Applying neural networks in the process industries has now become well established. Process and control engineers have started to appreciate the merits of deploying neural networks for process modeling and control. The best established application is probably inferential property estimation, also known as inferential sensing or soft sensing. More recently, model predictive control applications using neural network technology have been emerging. No matter what the final application is, the first step in using a neural network is to create a process model using plant data. This sounds simple at the outset, but preparing data for modeling is a science in itself. Several details should

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