重庆理工大学学报（自然科学版）2016，Vol.30Issue(6)：96-101,6.DOI:10.3969/j.issn.1674-8425(z).2016.06.016
基于主成分分析与 BP 神经网络的桑椹黄酮提取含量建模研究
Research on Modeling of Flavonoids Extraction Content of Mulberry Based on Principal Component Analysis and BP Artificial Neural Networks
摘要
Abstract
At present,determination of flavonoids extraction content of mulberry is mostly done manually,which is difficult to be predicted.A scientific and rapid prediction model was created through combining principal component analysis with BP artificial neural network.Data of 4 factors influencing the flavonoids extraction content of mulberry was obtained through experiments,and 3 principal components were extracted after principal component analysis of above data.BP artificial neural network was trained with above 3 principal components as input data,and then flavonoids extraction content of mulberry can be predicted through the trained BP artificial neural network. Experiment result shows that the prediction model has high prediction accuracy,so using principal component analysis and BP artificial neural network to predict flavonoids extraction content of mulberry is effective.关键词
桑椹/黄酮/提取含量/主成分分析/BP神经网络Key words
mulberry/flavonoid/extraction content/principal component analysis/BP artificial neural network分类
医药卫生引用本文复制引用
陈桂芬,王英豪,王兴..基于主成分分析与 BP 神经网络的桑椹黄酮提取含量建模研究[J].重庆理工大学学报（自然科学版）,2016,30(6):96-101,6.基金项目
福建省自然科学基金资助项目（2013J01377）；福建省教育厅 A 类项目 （）
