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
Log in to view this article.
Not Yet A Subscriber? Here are Your Options.
1) Start a FREE TRIAL SUBSCRIPTION and gain access to all articles in the current issue of Hydrocarbon Processing magazine.
2) SUBSCRIBE to Hydrocarbon Processing magazine in print or digital format and gain ACCESS to the current issue as well as to 3 articles from the HP archives per month. $409 for an annual subscription*.
3) Start a FULL ACCESS PLAN SUBSCRIPTION and regain ACCESS to this article, the current issue, all past issues in the HP Archive, the HP Process Handbooks, HP Market Data, and more. $1,995 for an annual subscription. For information about group rates or multi-year terms, contact email Peter Ramsay or call +44 20 3409 2240*.
*Access will be granted the next business day.