Study on Recognition and Classificationof Blood Fluorescence Spectrum with BP Neural Network
GAO Bin1, ZHAO Peng-fei1, LU Yu-xin1, FAN Ya1, ZHOU Lin-hua1*, QIAN Jun2, LIU Lin-na2, ZHAO Si-yan2, KONG Zhi-feng3
1. School of Science, Changchun University of Science and Technology, Changchun 130022, China
2. Changchun Veterinary Institute, Chinese Academic Agricultural Sciences, Changchun 130122, China
3. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710048, China
Abstract：There is no doubt that spectrum technology has a positive role in applied prospects of biological and medical testing. Because of the complexity and the similarity ofblood component, study on recognition and classificationof different animal’s blood is still an open issue. Based on the theory of machine learning, by BP neural network, the authorsproposed a methodoffeature extraction and classification for different animal’s blood fluorescence spectra. In this experiment, fluorescence spectra data of whole blood and red blood cell with different concentration (1% and 3%) is collected, respectively. By neighborhood average method, the original data is denoised in order to reduce the impact of noiseon thefeature extraction and classification. For the specialty of blood fluorescence spectra, the authors proposed a new feature extraction method of “Combination and Amplification method”, and established a BP neural network classifier. Compared with other common spectrafeature, “Combination and Amplification”feature and the BP neural network classifiercan achieve good recognition and classification for different animal’s blood fluorescence spectra, and the test error is much less than allowable variation. The technologies in this paper can play an important role inmedical examination, agriculture, and food safety testing.
Key words：Fluorescence spectra; Blood spectrum recognition; BP neural network; Combination and amplification method
高 斌，赵鹏飞，卢昱欣，范 雅，周林华，钱 军，刘林娜，赵思言，孔之丰. 基于BP神经网络的血液荧光光谱识别分类研究[J]. 光谱学与光谱分析, 2018, 38(10): 3136-3143.
GAO Bin, ZHAO Peng-fei, LU Yu-xin, FAN Ya, ZHOU Lin-hua, QIAN Jun, LIU Lin-na, ZHAO Si-yan, KONG Zhi-feng. Study on Recognition and Classificationof Blood Fluorescence Spectrum with BP Neural Network. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(10): 3136-3143.
