October 2008


Process modeling and optimization strategies integrating neural networks and differential evolution

The technology was applied to an ethylene oxide reactor

Garawi, M. A., Khalfe, N., Lahiri, S. K., National Institute of Technology

This article presents an artificial intelligence-based process modeling and optimization strategy, namely artificial neural networks¡ªdifferential evolution (ANN-DE) for modeling and optimizing catalytic industrial ethylene oxide (EO) reactors. In the ANN-DE approach, an ANN model is constructed for correlating process data comprising values of operating and performance variables. Next, model inputs describing process operating variables are optimized using DEs with a view to maximizing the process performance. The DE possesses certain unique advantages over the commonly used gradient-based deterministic optimization algorithms. The ANN-DE is a new strategy for chemical process mod

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