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An approximate modelling method for industrial l-lysine fermentation process

Citation

Wang, H and Khan, FI and Chen, B and Lu, Z, An approximate modelling method for industrial l-lysine fermentation process, Computer Aided Chemical Engineering, 37 pp. 461-466. ISSN 1570-7946 (2015) [Refereed Article]

Copyright Statement

Copyright 2015 Elsevier B.V.

DOI: doi:10.1016/B978-0-444-63578-5.50072-4

Abstract

l-lysine is an important chemical, usually produced by fed-batch fermentation process. Usually, feed stock compositions, reactant or product concentrations, and operating conditions vary with different fed-batches in this process. It is difficult to establish a kinetics-based model for an industrial fed-batch fermentation process. In this paper, we proposed a data-based approximate graphical modelling method to model this process. Variables values are treated as correlated Gaussian process. The methodology comprises of two important steps: i) the missing-data imputation within records, and ii) the dynamic Bayesian network learning, including structure learning, using the low order conditional independence method, and parameters learning, using the multivariate auto regressive method. The l-lysine fed-batch fermentation process is studied to demonstrate the effectiveness of this approximate modelling method.

Item Details

Item Type:Refereed Article
Keywords:dynamic Bayesian network, fed-batch fermentation, Gaussian approximate; L-lysine, missing-data imputation
Research Division:Engineering
Research Group:Interdisciplinary Engineering
Research Field:Risk Engineering (excl. Earthquake Engineering)
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Engineering
Author:Khan, FI (Professor Faisal Khan)
ID Code:120656
Year Published:2015
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-30
Last Modified:2017-11-06
Downloads:0

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