摘要
目的:使用BP神经网络结合遗传算法用于秦皮提取工艺的多目标优化。方法:以秦皮甲素和秦皮乙素为指标,采用均匀设计法优化BP神经网络模型参数,并建立网络模型,再利用遗传算法对网络进行多目标寻优,获得秦皮的最佳提取工艺。结果:得到的最优工艺条件为提取温度99℃、乙醇体积分数50%、液固比7、提取时间94 min,网络在此条件下的预测值为秦皮甲素提取量为9.617 mg.g-1,秦皮乙素提取量为2.195 mg.g-1,和实际测量值的相对误差仅为-1.16%和-5.14%,具有较好的网络预测性。结论:BP神经网络结合遗传算法可用于秦皮提取工艺的多目标优化。
Objective： To introduce Back-propagation （BP） neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini. Method： BP neural network was established and optimized with uniform design. Genetic algotithm was used for multi-objective optimization of extraction technology of cortex fraxini. Result： the optimization of extraction was as follows ： extraction temperature was 99 ℃, concentration of EtOH was 50%, liquid-solid ratio was 7, extraction time was 94 min. The proportional error between predictive value and practical measured value was just - 1.16% and - 5.14%. Conclusion： Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of cortex fraxini is advisable.
出处
《中国中药杂志》
CAS
CSCD
北大核心
2008年第22期2622-2626,共5页
China Journal of Chinese Materia Medica
关键词
秦皮
提取工艺
均匀设计
BP神经网络
遗传算法
多目标优化
Cortex Fraxini
extraction technology
uniform design method
back-propagation （BP） neural network
genetic algorithm
multi-objective optimization
