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A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework
Department of Chemical Engineering, University of Maiduguri, Maiduguri, Nigeria
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- 2 Department of Chemical Engineering, University of Maiduguri, Maiduguri, Nigeria
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Advances in Chemical Engineering and Science·Volume 03 (2013)·Pages 164–170·Published 29 April 2013·DOI10.4236/aces.2013.32020
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Abstract
This paper presents a comprehensive review of various traditional systems of crude oil distillation column design, modeling, simulation, optimization and control methods. Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column. It was discovered that many past researchers used rigorous simulations which led to convergence p roblems that were time consuming. The use of dynamic mathematical models was also challenging as these models wer e also time dependent. The proposed methodologies use back-propagation algorithm to replace the convergence problem using error minimal method.
KeywordsArtificial Neural NetworkCrude Oil Distillation ColumnGenetic Algorithm FrameworkSigmoidal Transfer FunctionBack-Propagation Algorithm
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