| 光谱学与光谱分析 |
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| Identification of Rhubarb Samples Based on IR Spectra by Using Takagi-Sugeno Fuzzy Systems |
| TANG Yan-feng1, ZHANG Zhuo-yong1*, FAN Guo-qiang2 |
1. Department of Chemistry Resources Environment and GIS Key Lab of Beijing, Capital Normal University, Beijing 100037, China
2. Institute for Chinese Medicine, Beijing Tongrentang Group Co. Ltd., Beijing 100011, China |
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Abstract Takagi-Sugeno fuzzy system is composed of several back-propagation neural networks (BP-NNs), and has some fuzzy logic properties. In this paper, the Takagi-Sugeno fuzzy logic system is applied to identifying official and unofficial rhubarb samples based on their infrared spectra. The effects of the number of hidden neurons and the momentum parameters on the prediction were investigated. The results obtained by using Takagi-Sugeno fuzzy system were better than those by commonly used BP-networks. With a proper network training parameter, 100% correctness can be obtained by using Takagi-Sugeno fuzzy system. This method is more accurate than the common methods, and is more scientific than traditional methods. So it is applied to identifying rhubarb easily and rapidly.
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Received: 2003-11-11
Accepted: 2004-03-26
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Corresponding Authors:
ZHANG Zhuo-yong
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| Cite this article: |
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TANG Yan-feng,ZHANG Zhuo-yong,FAN Guo-qiang. Identification of Rhubarb Samples Based on IR Spectra by Using Takagi-Sugeno Fuzzy Systems[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(04): 521-524.
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| URL: |
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https://www.gpxygpfx.com/EN/Y2005/V25/I04/521 |
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