| 人工神经网络用于中药材雷公藤和昆明山海棠的分类识别研究 |
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| 引用本文： | 张亮,蓝要武,韩英,张正行,安登魁.人工神经网络用于中药材雷公藤和昆明山海棠的分类识别研究[J].药学学报,1995,30(2):127-132. |
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| 作者姓名： | 张亮 蓝要武 韩英 张正行 安登魁 |
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| 作者单位： | 中国药科大学药物分析研究室，南京药物研究所植化室 |
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| 摘 要： | 应用误差反向传播学习算法(BP算法)对中药材雷公藤和昆明山海棠浸出物的红外光谱进行分类识别。网络为3层结构,输入节点为9个,隐层节点为21个,输出节点为1。分类结果与XIM-CA法基本一致。此外,本文还考察了网络参数间的相互关系。
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| 关 键 词： | 反向传播网络 雷公藤 昆明山海棠 |
| 收稿时间： | 1994-04-19 |
CLASSIFICATION AND RECOGNITION OF TRIPTERYGIUM WILFORDII AND T.HYPOGLAUCUM BY ARTIF101AL NEUKAL NETWORKS |
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| L Zhang,YW Lan,Y Han,ZX Zhang and DK An.CLASSIFICATION AND RECOGNITION OF TRIPTERYGIUM WILFORDII AND T.HYPOGLAUCUM BY ARTIF101AL NEUKAL NETWORKS[J].Acta Pharmaceutica Sinica,1995,30(2):127-132. |
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| Authors: | L Zhang YW Lan Y Han ZX Zhang and DK An |
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| Abstract: | A BASIC program for the simulation of artificial
neural networks was implementedon a 386SX. For classification and
recognition of infrared(IR) spectra of extracts by means of aneural
network, a back propagation model with one hidden layer and a sigmoid
transfer function hasbeen proved to be available. The nine features
selected by the Shannon information content were usedas input
elements. The hidden layer contains 21 nodes and the output layer
contains one node. |
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| Keywords: | Artificial neural network Ttipterygium wilfordii T hypoglaucum |
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