BP神经网络模型预测白芷超临界萃取结果的研究
神经,,神经网络；,超临界萃取；,白芷；,正交实验设计,1仪器和药品,2实验CO2方法,3实验CO2结果与BP神经网络模型,4讨论,参考文献：
摘要：目的用BP神经网络对白芷中香豆素类成分的超临界CO2萃取结果进行预测。方法以萃取压力、温度、时间、分离压力、药材粉碎度为网络的输入向量，以总香豆素、氧化前胡素和欧前胡素作为网络的输出，建立BP神经网络模型，利用正交实验数据对网络进行训练。结果得到一个结构为5×4×3的2层BP网络，测试样本的实际测量值与网络的输出吻合很好。结论可利用正交实验数据对BP网络进行训练，利用训练好的网络对中药药效物质基础的超临界萃取结果进行预测。关键词：神经网络； 超临界萃取； 白芷； 正交实验设计
Forecasting the Extraction of Coumarins in Angelica dahurica by Supercritical CO2 with BP Neural Network
LIU Hongmei
(College of Biochemical Engineering of Beijing Union University, Beijing 100023, China)
Abstract:ObjectiveTo predict the extraction results of coumarins in Angelica dahurica by supercritical CO2 using back-propagation neural network. MethodsBP neural network model was established by taking extraction pressure, temperature and time as well as separation pressure and pulverized degree as the inputs of network and the contents of oxyimperatorin, imperatorin and the overall coumarins in the extract as outputs of neural network. BP network was trained with Orthogonal experimental results. ResultsA 5×4×3 neural network has been set up. The forecasted profiles based on BP-NN model were closely similar to the target values. ConclusionOrthogonal experimental results could be used to training BP-NN and the trained BP-NN could forecast the extraction results of active components in Chinese herb medicines. ......
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