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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ump-60162015-03-03T09:27:58Z http://umpir.ump.edu.my/id/eprint/6016/ 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 efficiency 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. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6016/1/Stochastic_Growth_Logistic_Model_with_Aftereffect_for_Batch.pdf 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. In: Proceedings of the 3rd International Conference on Mathematical Sciences, 17-19 December 2013 , Kuala Lumpur. pp. 1168-1177.. http://dx.doi.org/10.1063/1.4882632 |
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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 |
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 efficiency 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 |
Conference or Workshop Item |
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 |
title |
Stochastic Growth Logistic Model with Aftereffect for Batch
Fermentation Process
|
title_short |
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_sort |
stochastic growth logistic model with aftereffect for batch
fermentation process |
publishDate |
2014 |
url |
http://umpir.ump.edu.my/id/eprint/6016/ http://umpir.ump.edu.my/id/eprint/6016/ http://umpir.ump.edu.my/id/eprint/6016/1/Stochastic_Growth_Logistic_Model_with_Aftereffect_for_Batch.pdf |
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2023-09-18T22:01:31Z |
last_indexed |
2023-09-18T22:01:31Z |
_version_ |
1777414429560799232 |