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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Bibliographic Details
Main Authors: Rosli Norhayati, Ayoubi Tawfiqullah, Arifah, Bahar, Rahman, Haliza Abdul, Salleh Madihah Md
Format: Conference Proceeding
Language:English
Subjects:
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
COMPARATIVE EVALUATIONS
Computer simulation
FERMENTATION
LEAST SQUARE FIT
MATHEMATICAL MODELS
MATHEMATICAL SOLUTIONS
Microorganisms
NONLINEAR PROBLEMS
OPTIMIZATION
Root-mean-square errors
Solvents
Stochastic models
STOCHASTIC PROCESSES
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Summary: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.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4882632