L-异亮氨酸发酵培养基的遗传算法优化及发酵过程的神经网络建模  

Genetic Algorithms Optimization of L-Ile Fermentation Medium and Modeling by Neural Network

作　　者：宋文军[1] 陈宁[1] 熊明勇[1] 魏春[1] 张克旭[1] 

机构地区：[1]天津科技大学食品科学与生物工程学院,天津300222

出　　处：《天津师范大学学报（自然科学版）》2003年第1期46-50,共5页Journal of Tianjin Normal University：Natural Science Edition

基　　金：天津科技大学基金资助项目(2002-289)

摘　　要：应用遗传算法对L-异亮氨酸发酵培养基进行优化,经优化后的发酵培养基能积累L-异亮氨酸16.84g/L,比初始值提高28.7%.并且运用神经网络对L-异亮氨酸的发酵过程进行建模并预测,取得了良好的效果.结果表明,神经网络在L-异亮氨酸发酵的模拟与预测中是一种高效快速的方法.The fermentation medium of Lisoleucine was optimized by genetic algorithms, which could accumulate Lisoleucine concentration to 16.84 g/L and was higher 28.7% than initial value. The backpropagation neural network was applied to the modeling and predication on the process of Lisoleucine fermentation,which obtained an upstanding effect.The results indicated that the backpropagation was an effective and quick method for simulation and predication on the process of Lisoleucine fermentation.

关 键 词：遗传算法 神经网络 L-异亮氨酸 优化 建模 

分 类 号：TQ922.9[轻工技术与工程—发酵工程]