Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network

General porosity prediction models of food during air-drying have been developed using regression analysis and hybrid neural network techniques. Porosity data of apple, carrot, pear, potato, starch, onion, lentil, garlic, calamari, squid, and celery were used to develop the model using 286 data poin...

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Main Authors:	Hussain, Mohd Azlan, Rahman, M.S., Ng, C.W.
Format:	Article
Published:	Elsevier 2002
Subjects:	TA Engineering (General). Civil engineering (General) TP Chemical technology
Online Access:	http://eprints.um.edu.my/7072/ https://doi.org/10.1016/S0260-8774(01)00063-2
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Institution:	Universiti Malaya

id	my.um.eprints.7072
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spelling	my.um.eprints.70722021-02-10T03:38:46Z http://eprints.um.edu.my/7072/ Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network Hussain, Mohd Azlan Rahman, M.S. Ng, C.W. TA Engineering (General). Civil engineering (General) TP Chemical technology General porosity prediction models of food during air-drying have been developed using regression analysis and hybrid neural network techniques. Porosity data of apple, carrot, pear, potato, starch, onion, lentil, garlic, calamari, squid, and celery were used to develop the model using 286 data points obtained from the literature. The best generic model was developed based on four inputs as temperature of drying, moisture content, initial porosity, and product type. The error for predicting porosity using the best generic model developed is 0.58, thus identified as an accurate prediction model. Â© 2001 Elsevier Science Ltd. All rights reserved. Elsevier 2002 Article PeerReviewed Hussain, Mohd Azlan and Rahman, M.S. and Ng, C.W. (2002) Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network. Journal of Food Engineering, 51 (3). pp. 239-248. ISSN 0260-8774 https://doi.org/10.1016/S0260-8774(01)00063-2 doi:10.1016/S0260-8774(01)00063-2
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	TA Engineering (General). Civil engineering (General) TP Chemical technology
spellingShingle	TA Engineering (General). Civil engineering (General) TP Chemical technology Hussain, Mohd Azlan Rahman, M.S. Ng, C.W. Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network
description	General porosity prediction models of food during air-drying have been developed using regression analysis and hybrid neural network techniques. Porosity data of apple, carrot, pear, potato, starch, onion, lentil, garlic, calamari, squid, and celery were used to develop the model using 286 data points obtained from the literature. The best generic model was developed based on four inputs as temperature of drying, moisture content, initial porosity, and product type. The error for predicting porosity using the best generic model developed is 0.58, thus identified as an accurate prediction model. Â© 2001 Elsevier Science Ltd. All rights reserved.
format	Article
author	Hussain, Mohd Azlan Rahman, M.S. Ng, C.W.
author_facet	Hussain, Mohd Azlan Rahman, M.S. Ng, C.W.
author_sort	Hussain, Mohd Azlan
title	Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network
title_short	Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network
title_full	Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network
title_fullStr	Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network
title_full_unstemmed	Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network
title_sort	prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network
publisher	Elsevier
publishDate	2002
url	http://eprints.um.edu.my/7072/ https://doi.org/10.1016/S0260-8774(01)00063-2
_version_	1691733422576238592

Prediction of pores formation (porosity) in foods during drying: generic models by the use of hybrid neural network

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