Optimization of a fermentation medium using neural networks and genetic algorithms

被引：113
|
作者：
Nagata, Y [1 ]
Chu, KH [1 ]
机构：
[1] Univ Canterbury, Dept Chem & Proc Engn, Christchurch 1, New Zealand
来源：
BIOTECHNOLOGY LETTERS | 2003年 / 25卷 / 21期
关键词：
artificial neural network; genetic algorithm; medium optimization; response surface methodology;
D O I：
10.1023/A:1026225526558
中图分类号：
Q81 [生物工程学（生物技术）]; Q93 [微生物学];
学科分类号：
071005 ; 0836 ; 090102 ; 100705 ;
摘要：
Artificial neural networks and genetic algorithms are used to model and optimize a fermentation medium for the production of the enzyme hydantoinase by Agrobacterium radiobacter. Experimental data reported in the literature were used to build two neural network models. The concentrations of four medium components served as inputs to the neural network models, and hydantoinase or cell concentration served as a single output of each model. Genetic algorithms were used to optimize the input space of the neural network models to find the optimum settings for maximum enzyme and cell production. Using this procedure, two artificial intelligence techniques have been effectively integrated to create a powerful tool for process modeling and optimization.
引用
收藏
页码：1837 / 1842
页数：6
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