摘要
利用AB-8大孔树脂对甘草黄酮动态吸附条件进行优化,并通过BP神经网络对试验数据进行建模,利用遗传算法优化所建立的BP神经网络,以模拟甘草黄酮动态吸附过程。结果表明:上柱液黄酮质量浓度2.1 mg/mL,流速327 r/min,pH4.8,在此条件下附率可达93.12%;经遗传算法优化的BP神经网络训练后可应用于甘草黄酮动态吸附过程的模拟。
The AB-8 macroporous resin on the licorice flavonoids dynamic adsorption conditions was studied. The mathematic model was established by the BP neural network on the basis of experimental data, the BP neural network which could be used to simulate the dynamic adsorption process of licorice flavonoids was optimized by genetic algorithm. The results showed that the adsorption rate could reach 93.12% under these conditions： the column liquid concentration on 2.1 mg/mL, velocity 327 r/min, pH 4.8. The trained BP neural network which was optimized by genetic algorithm could be applied to simulate the dynamic adsorption process of licorice flavonoids.
出处
《食品工业》
北大核心
2013年第5期136-138,共3页
The Food Industry
关键词
甘草黄酮
响应面分析
神经网络
遗传算法
licorice flavonoids
response surface analysis
neural network
genetic algorithm
