DRIFT ANALYSIS ON NEURAL NETWORK MODEL OF HEAT EXCHANGER FOULING
Neural Networks (NN) provide a good platform for modeling complex and poorly understood systems in many different fields. Due to the empirical nature of NN, it is typically valid only for small operating windows. As the process drifts, the prediction accuracy of such models deteriorates very much re...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/3728/1/048-061.pdf http://www.doaj.org/doaj?func=abstract&id=665418 http://eprints.utp.edu.my/3728/ |
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