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 Lisoleucine was optimized by genetic algorithms, which could accumulate Lisoleucine 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 Lisoleucine fermentation,which obtained an upstanding effect.The results indicated that the backpropagation was an effective and quick method for simulation and predication on the process of Lisoleucine fermentation.
出处
《天津师范大学学报（自然科学版）》
CAS
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)
关键词
遗传算法
神经网络
L-异亮氨酸
优化
建模
genetic algorithms
neural network
L-isoleucine
optimize
modeling
