| 光谱学与光谱分析 |
|
|
|
|
|
| Radial Basis Function Networks and IR Spectrometry Applied for Identification of Official Rhubarb Samples |
| MA Shu-min1, LIU Si-dong1, ZHANG Zhuo-yong2*, FAN Guo-qiang3 |
1. Faculty of Chemistry, Northeast Normal University, Changchun 130024, China
2. Department of Chemistry, Capital Normal University, Beijing 100037, China
3. Institute for Chinese Medicine, Beijing Tongrentang Group Co. Ltd., Beijing 100011, China |
|
|
|
|
Abstract The Fourier transform infrared spectrometry (FTIRS) and radial basis function neural network (RBF-NN) have been applied to develop classification models for identifying official and unofficial rhubarb samples. The original data were compressed from 775 variables to 49 variables by using wavelet transformation method. The compressed spectra with reduced variables maintain the characteristics of the IR spectra and speed up the network training process. The effects of network parameters including error goal and spread constant, were investigated. The rate of correct classification is up to 97.78% at optimized conditions. Results show that the combination of IRS and ANN can be used as fast and convenient tool for identification of Chinese herbal samples.
|
|
Received: 2003-12-06
Accepted: 2004-04-26
|
|
|
|
Corresponding Authors:
ZHANG Zhuo-yong
|
|
| Cite this article: |
|
MA Shu-min,LIU Si-dong,ZHANG Zhuo-yong, et al. Radial Basis Function Networks and IR Spectrometry Applied for Identification of Official Rhubarb Samples[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(06): 874-877.
|
|
|
|
| URL: |
|
https://www.gpxygpfx.com/EN/Y2005/V25/I06/874 |
[1] SUN Su-qin, LIU Jun, ZHOU Qun(孙素琴，刘 军，周 群). Chinese Journal of Analytical Chemistry(分析化学)，2002，30(2)：140.
[2] GU Jin, LIU Ping(古 今，刘 萍). Pharm. J. Chin. PLA(解放军药学学报)，2002，18(4)：223.
[3] WANG Xu-ming, ZHAO Qing-hua, LIANG Ai-jun(王绪明，赵庆华，梁爱君). Pharm. J. Chin. PLA(解放军药学学报)，1999，15(2)：24.
[4] ZHANG Hong-xing, DUAN Yong-hong(张红星，段永红). Henan Journal of Traditional Drugs(河南中医药学刊), 2002，17(5)：11.
[5] Shaw P C, But P P H. Planta. Med., 1995, 61: 466.
[6] SUN Su-qin, TANG Jun-ming, YUAN Zi-min, BAI Yan(孙素琴，汤俊明，袁子民，白 雁). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2003, 23(2): 258.
[7] XU Yong-qun, SUN Su-qin, FENG Xue-feng, HU Shi-lin(徐永群，孙素琴，冯学峰，胡世林). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2003, 23(3): 502.
[8] ZHOU Qun, SUN Su-qin, LEUNG Hi-win(周 群，孙素琴，梁曦云). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2003, 23(3): 509.
[9] HUANG Hao, SUN Su-qin, XU Jin-wen, WANG Zhao(黄 昊，孙素琴，许锦文，王 钊). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2003, 23(2): 253.
[10] YE Li-na, LUO Ai-qin, FU Ruo-nong, et al(耶利娜，罗爱芹，傅若农，等). Chinese Journal of Analytical Chemistry(分析化学), 2000, 28(5): 549.
[11] ZHANG Zhuo-yong, WANG Dan, Peter de B Harrington, Kent J Voorhees, Jon rees(张卓勇，王 丹, Peter de B Harrungton, Kent J Voorhees, Jon Ress). Computers and Applied Chemistry(计算机与应用化学)，2002，19(1)：45.
[12] LIU Si-dong, CUI Xiu-jun, ZHANG Zhuo-yong, GUO Ying-na, YE Han-feng, DING Yun-zheng(刘思东，崔秀君，张卓勇，郭英娜，叶汉峰，丁蕴铮). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2003，23(1)：119.
[13] Blanco M, Coello J, Iturriaga H, Maspoch S, Pages J. Chemometrics and Intelligent Laboratory Systems., 2000, 50: 75.
[14] TANG Yan-feng, ZHANG Zhuo-yong, FAN Guo-qiang(汤彦丰，张卓勇，范国强). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2004，24(11)：1348.
|
| [1] |
GUO Ya-fei1, CAO Qiang1, YE Lei-lei1, ZHANG Cheng-yuan1, KOU Ren-bo1, WANG Jun-mei1, GUO Mei1, 2*. Double Index Sequence Analysis of FTIR and Anti-Inflammatory Spectrum Effect Relationship of Rheum Tanguticum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 188-196. |
| [2] |
XU Rong1, AO Dong-mei2*, LI Man-tian1, 2, LIU Sai1, GUO Kun1, HU Ying2, YANG Chun-mei2, XU Chang-qing1. Study on Traditional Chinese Medicine of Lonicera L. Based on Infrared Spectroscopy and Cluster Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3518-3523. |
| [3] |
DONG Jian-jiang1, TIAN Ye1, ZHANG Jian-xing2, LUAN Zhen-dong2*, DU Zeng-feng2*. Research on the Classification Method of Benthic Fauna Based on
Hyperspectral Data and Random Forest Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3015-3022. |
| [4] |
JIA Zong-chao1, WANG Zi-jian1, LI Xue-ying1, 2*, QIU Hui-min1, HOU Guang-li1, FAN Ping-ping1*. Marine Sediment Particle Size Classification Based on the Fusion of
Principal Component Analysis and Continuous Projection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3075-3080. |
| [5] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
| [6] |
WEI Zi-kai, WANG Jie, ZHANG Ruo-yu, ZHANG Meng-yun*. Classification of Foreign Matter in Cotton Using Line Scan Hyperspectral Transmittance Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3230-3238. |
| [7] |
MA Qian1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, CHENG Hui-zhu1, 2, ZHAO Yan-chun1, 2. Research on Classification of Heavy Metal Pb in Honeysuckle Based on XRF and Transfer Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2729-2733. |
| [8] |
YANG Sen1, ZHANG Xin-ao1, XING Jian1, DAI Jing-min2. Study on Multi-Feature Model Fusion Variety Classification and Multi-Parameter Appearance Inspection for Milled Rice[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2837-2842. |
| [9] |
JIN Chun-bai1, YANG Guang1*, LU Shan2*, LIU Wen-jing1, LI De-jun1, ZHENG Nan1. Band Selection Method Based on Target Saliency Analysis in Spatial Domain[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2952-2959. |
| [10] |
PU Shan-shan, ZHENG En-rang*, CHEN Bei. Research on A Classification Algorithm of Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2446-2451. |
| [11] |
FAN Ya-wen, LIU Yan-ping*, QIU Bo, JIANG Xia, WANG Lin-qian, WANG Kun. Research on Spectral Classification of Stellar Subtypes Based on
SSTransformer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2523-2528. |
| [12] |
TANG Ting, PAN Xin*, LUO Xiao-ling, GAO Xiao-jing. Fusion of ConvLSTM and Multi-Attention Mechanism Network for
Hyperspectral Image Classification[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2608-2616. |
| [13] |
LI Chen-xi1, SUN Ze-yu1, 2, ZHAO Yu2*, YIN Li-hui2, CHEN Wen-liang1, 3, LIU Rong1, 3, XU Ke-xin1, 3. The Research Progress of Two-Dimensional Correlation Spectroscopy and Its Application in Protein Substances Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 1993-2001. |
| [14] |
JIANG Xia*, QIU Bo, WANG Lin-qian, GUO Xiao-yu. Automatic Classification Method of Star Spectra Based on
Semi-Supervised Mode[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1875-1880. |
| [15] |
WU Chao1, QIU Bo1*, PAN Zhi-ren1, LI Xiao-tong1, WANG Lin-qian1, CAO Guan-long1, KONG Xiao2. Application of Spectral and Metering Data Fusion Algorithm in Variable Star Classification[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1869-1874. |
|
|
|
|
