摘要
运用BP神经网络对L 色氨酸的发酵过程进行建模并预测,所建立的模型能够比较精确地模拟菌体生长、底物消耗以及发酵产酸3个过程的变化。结果表明,BP神经网络在L 色氨酸发酵的模拟与预测中是一种高效快速的方法。
The backpropagation neural network was applied to modeling and predication on process of Ltryptophan fermentation.The model can imitate precisely the process of bacteria growth, base consumption and products. The results indicated that the backpropagation was an effective and quick method for simulation and predication on process of Ltryptophan fermentation.
出处
《天津轻工业学院学报》
2003年第3期1-4,共4页
Journal of Tianjin University of Light Industry
基金
天津市科委攻关项目(983113711)
