Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt o...

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Main Authors: Norhayati, Rosli, Tawfiqullah, Ayoubi, Arifah, Bahar, Haliza, Abdul Rahman, Madihah, Md Salleh
Format: Article
Published: AIP Publishing LLC 2014
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Online Access:http://umpir.ump.edu.my/id/eprint/8982/
http://dx.doi.org/10.1063/1.4882632
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author Norhayati, Rosli
Tawfiqullah, Ayoubi
Arifah, Bahar
Haliza, Abdul Rahman
Madihah, Md Salleh
author_facet Norhayati, Rosli
Tawfiqullah, Ayoubi
Arifah, Bahar
Haliza, Abdul Rahman
Madihah, Md Salleh
author_sort Norhayati, Rosli
building UMPSA Library
collection Institutional Repository
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
continent Asia
country Malaysia
description In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.
format Article
id my.ump.umpir.8982
institution Universiti Malaysia Pahang
publishDate 2014
publisher AIP Publishing LLC
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spelling my.ump.umpir.89822016-06-27T06:54:13Z http://umpir.ump.edu.my/id/eprint/8982/ Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process Norhayati, Rosli Tawfiqullah, Ayoubi Arifah, Bahar Haliza, Abdul Rahman Madihah, Md Salleh Q Science (General) In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits. AIP Publishing LLC 2014 Article PeerReviewed Norhayati, Rosli and Tawfiqullah, Ayoubi and Arifah, Bahar and Haliza, Abdul Rahman and Madihah, Md Salleh (2014) Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process. AIP Conf. Proc. : Proceedings of the 3rd International Conference On Mathematical Sciences, 1602. pp. 1168-1177. ISSN 978-0-7354-1236-1. (Published) http://dx.doi.org/10.1063/1.4882632 DOI: 10.1063/1.4882632
spellingShingle Q Science (General)
Norhayati, Rosli
Tawfiqullah, Ayoubi
Arifah, Bahar
Haliza, Abdul Rahman
Madihah, Md Salleh
Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process
title Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process
title_full Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process
title_fullStr Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process
title_full_unstemmed Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process
title_short Stochastic Growth Logistic Model With Aftereffect for Batch Fermentation Process
title_sort stochastic growth logistic model with aftereffect for batch fermentation process
topic Q Science (General)
url http://umpir.ump.edu.my/id/eprint/8982/
http://dx.doi.org/10.1063/1.4882632
url_provider http://umpir.ump.edu.my/