Modeling of tapioca starch hydrolysis using neural networks

This paper considers the use of neural network models to represent the dynamic behavior of glucoamylase-starch system. The model studied in this research is multilayered feed-forward structure with time delay. In this paper we give preliminary results on the modeling adequacy of the neural network m...

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Main Authors: Rashid, Roslina, Saidina Amin, Nor Aishah, Jamaluddin, Hishamuddin
Format: Article
Language:English
Published: Faculty of Chemical and Natural Resources Engineering, UTM 2001
Subjects:
Online Access:http://eprints.utm.my/5069/
http://eprints.utm.my/5069/1/RoslinaRashid2001_ModelingOfTapiocaStarchHydrolysis.pdf
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author Rashid, Roslina
Saidina Amin, Nor Aishah
Jamaluddin, Hishamuddin
author_facet Rashid, Roslina
Saidina Amin, Nor Aishah
Jamaluddin, Hishamuddin
author_sort Rashid, Roslina
building UTeM Institutional Repository
collection Online Access
description This paper considers the use of neural network models to represent the dynamic behavior of glucoamylase-starch system. The model studied in this research is multilayered feed-forward structure with time delay. In this paper we give preliminary results on the modeling adequacy of the neural network models. Data for the training were obtained from Bioprocess Laboratory, UTM. It was found that, the model was successfully developed using multilayered structure of neural network and the model exhibited satisfactory results. It is concluded that neural network technique is a feasible tool for model development of tapioca starch hydrolysis. Further modification of the structure such as increasing the time delay is also recommended for encouraging results.
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publishDate 2001
publisher Faculty of Chemical and Natural Resources Engineering, UTM
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spelling utm-50692010-06-01T03:23:13Z http://eprints.utm.my/5069/ Modeling of tapioca starch hydrolysis using neural networks Rashid, Roslina Saidina Amin, Nor Aishah Jamaluddin, Hishamuddin T Technology (General) This paper considers the use of neural network models to represent the dynamic behavior of glucoamylase-starch system. The model studied in this research is multilayered feed-forward structure with time delay. In this paper we give preliminary results on the modeling adequacy of the neural network models. Data for the training were obtained from Bioprocess Laboratory, UTM. It was found that, the model was successfully developed using multilayered structure of neural network and the model exhibited satisfactory results. It is concluded that neural network technique is a feasible tool for model development of tapioca starch hydrolysis. Further modification of the structure such as increasing the time delay is also recommended for encouraging results. Faculty of Chemical and Natural Resources Engineering, UTM 2001 Article PeerReviewed application/pdf en http://eprints.utm.my/5069/1/RoslinaRashid2001_ModelingOfTapiocaStarchHydrolysis.pdf Rashid, Roslina and Saidina Amin, Nor Aishah and Jamaluddin, Hishamuddin (2001) Modeling of tapioca starch hydrolysis using neural networks. Proceedings of The 15th Symposium of Malaysian Chemical Engineers SOMChE 2001 . pp. 461-465.
spellingShingle T Technology (General)
Rashid, Roslina
Saidina Amin, Nor Aishah
Jamaluddin, Hishamuddin
Modeling of tapioca starch hydrolysis using neural networks
title Modeling of tapioca starch hydrolysis using neural networks
title_full Modeling of tapioca starch hydrolysis using neural networks
title_fullStr Modeling of tapioca starch hydrolysis using neural networks
title_full_unstemmed Modeling of tapioca starch hydrolysis using neural networks
title_short Modeling of tapioca starch hydrolysis using neural networks
title_sort modeling of tapioca starch hydrolysis using neural networks
topic T Technology (General)
url http://eprints.utm.my/5069/
http://eprints.utm.my/5069/1/RoslinaRashid2001_ModelingOfTapiocaStarchHydrolysis.pdf