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Tikrit Journal of Engineering Sciences (2015) 22(1) 24- 37

Development of Artificial Neural Network Model of Crude Oil Distillation Column

Duraid Fadhil Ahmed Ali Hussein Khalaf
Chemical Eng. Dept., Tikrit University, Iraq

Abstract

Artificial neural network in MATLAB simulator is used to model Baiji crude oil distillation unit based on data generated from aspen-HYSYS simulator. Thirteen inputs, six outputs and over 1487 data set are used to model the actual unit. Nonlinear autoregressive network with exogenous inputs (NARX) and back propagation algorithm are used for training. Seventy percent of data are used for training the network while the remaining thirty percent are used for testing and validating the network to determine its prediction accuracy. One hidden layer and 34 hidden neurons are used for the proposed network with MSE of 0.25 is obtained. The number of neuron are selected based on less MSE for the network. The model founded to predict the optimal operating conditions for different objective functions within the training limit since ANN models are poor extrapolators. They are usually only reliable within the range of data that they had been trained for

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Keywords: Artificial Neural Network Model, Crude Oil Distillation Unit, MATLAB, Aspen-HYSYS.

How to cite

TJES: Ahmed DF, Khalaf AH. Development of Artificial Neural Network Model of Crude Oil Distillation Column. Tikrit Journal of Engineering Sciences 2015;22(1):24-37.
APA: Ahmed, D. F., & Khalaf, A. H. (2015). Development of Artificial Neural Network Model of Crude Oil Distillation Column. Tikrit Journal of Engineering Sciences, 22(1), 24-37.