Feed Forward Neural Network Model for Isopropyl Myristate Production in Industrial-scale Semi-batch Reactive Distillation Columns

Bashah, Nur Alwani Ali and Othman, Mohd Roslee and Aziz, Norashid (2015) Feed Forward Neural Network Model for Isopropyl Myristate Production in Industrial-scale Semi-batch Reactive Distillation Columns. Journal of Engineering Science and Technology, 11. pp. 59-65. ISSN 1823-4690

Preview

PDF Download (455kB) | Preview

Abstract

The application of the artificial neural network (ANN) model in chemical industries has grown due to its ability to solve complex model and online application problems. Typically, the ANN model is good at predicting data within the training range but is limited when predicting extrapolated data. Thus, in this paper, selected optimum multiple-input multiple-output (MIMO) and multiple-input single-output (MISO) models are used to predict the bottom (xb) compositions of extrapolated data. The MIMO and MISO models both managed to predict the extrapolated data with MSE values of 0.0078 and 0.0063 and with R2 values of 0.9986 and 0.9975, respectively.

Item Type:	Article
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1-2040 Engineering (General). Civil engineering (General)
Divisions:	Penerbit Universiti Sains Malaysia (USM Press) > Journal of Engineering Science
Depositing User:	Mr Firdaus Mohamad
Date Deposited:	30 Oct 2018 01:56
Last Modified:	30 Oct 2018 01:56
URI:	http://eprints.usm.my/id/eprint/42785

Actions (login required)

View Item