【摘要】 利用头孢菌素C发酵过程积累的数据,建立BP神经网络预估模型,实现以发酵前期的菌浓和pH对效价的预测,将此模型应用于生产实际,分别通过倒种和改变培养基中碳源组成的方法,使头孢菌素C的合成水平分别提高了11.8%和15.7%,表明模型具有较好的预测功能。更多还原

【Abstract】 The back propagation(BP) neural network model was set up by cephalosporin C fermentation data,and the productivity was forecasted by PMV and pH changing tendency of early fermentation phase.The model was proved to be effective and with good prediction capacity.By increasing inoculum and changing medium carbon source,the productivity of cephalosporin C fermentation was further increased by 11.8% and 15.7%,respectively,which was well predicted by the established model.更多还原