Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/394789
Title: Predictions of isolate and normal pentene of debutanizer catalytic reforming unit by using artificial neural network
Authors: Osman Ahmed Abdalla.
M. Nordin Zakaria
Suziah Sulaiman
Wan Fatimah Wan Ahmad
Conference Name: International Symposium on Information Technology 2008
Keywords: Predictions of isolate
Normal pentene
Debutanizer catalytic
Artificial neural network
Conference Date: 26/08/2008
Conference Location: Kuala Lumpur Convention Centre, Malaysia
Abstract: This paper presents a Iced-forward Artificial Neural Network (ANN) model for prediction of isolate and normal pentene of debutanizer catalytic reforming unit. Temperature, reflux flow, anti flow rate are used as input variables to the network. isolate pentene (iC5), and normal pentene (nC5) are employed as the output variable. About 500 field data collected from PETRONAS Penapisan (Melaka) Sdn Bhd were used to develop the ANN model. The developed ANN model obtained by dividing the collected data set into three different group: training, validation, and testing group. Back-propagation algorithm was used to train the network. A correlation coefficient of 0.999 was obtained with standard deviation of 0.006 for iC5. For nC5 a 0.999 correlation coefficient and 0.005 standard deviation obtained.
Pages: 6
Call Number: T58.5.C634 2008 kat sem
Publisher: Institute of Electrical and Electronics Engineers (IEEE),Piscataway, USA
Appears in Collections:Seminar Papers/ Proceedings / Kertas Kerja Seminar/ Prosiding

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