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題名 | A Robust Identification Model for Herbal Medicine Using Near Infrared Spectroscopy and Artificial Neural Network=應用近紅外光光譜與類神經網路於中草藥鑑別模式之建立 |
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作者 | 楊翕雯; 陳世銘; 歐陽孚; 楊宜璋; 蔡兆胤; | 書刊名 | Journal of Food and Drug Analysis |
卷期 | 19:1 2011.03[民100.03] |
頁次 | 頁9-17+103 |
分類號 | 413.1 |
關鍵詞 | 近紅外光; 類神經網路; 中草藥; Near infrared spectroscopy; NIR; Artificial neural network; ANN; Herbal medicine; |
語文 | 英文(English) |
英文摘要 | ABSTRACT A robust identification model for herbal medicine was developed by combining near-infrared spectroscopy (NIR) and artificial neural network (ANN) to discriminate raw materials of herbal medicine, which are often similar in appearance and practically impossible to identify by visual inspection alone. The identification by chemical methods is usually higher in cost and lower in efficiency. Compared with other modern inspection methods, NIR is an alternative, which is non-destructive, rapid, and easy to operate. In this study, we employed ANN to analyze the absorption spectra of herbal medicines and successfully built an identification model, which is able to identify 30 different herbal medicines. The best identification model can reach a correct identification rate (CIR) of 99.67% when applied to a training set of 600 samples, and 100% CIR when applied to a test set of 300 samples. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。