Acta Metrologica Sinica  2018, Vol. 39 Issue (5): 747-752    DOI: 10.3969/j.issn.1000-1158.2018.05.29
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Study on Fluorescence Spectrometric Detection of Potassium Sorbate Based on CS-SVM
WANG Shu-tao,ZHU Cai-yun,LIU Ming-xin, PENG Tao,CHENG Qi,KONG De-ming,WANG Yu-tian
Key Laboratory of Measurement Technology and Instrumentation, School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
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Abstract  By analyzing the fluorescence spectra of potassium sorbate in orange juice solution, it is found that fluorescence spectrum of potassium sorbate has glares where emission wavelength is in the range of 450~510nm when excitation wavelength is at 375nm, which indicates that the fluorescence characteristics of orange juice could interfere with the fluorescence spectrum of potassium sorbate. The model of cuckoo search algorithm (CS) optimizing support vector machine (SVM) is built to train 15 samples and predict the concentration of 7 potassium sorbate samples. The average recovery rate of CS-SVM is 99.07% and the mean square error is 1.21×10-5g/L. The results show that the training process,the average recovery and error of CS-SVM are all better than PSO-SVM and GA-SVM, and that CS-SVM can accurately determine the concentration of potassium sorbate in orange juice solution.
Key wordsmetrology      fluorescence spectroscopy      potassium sorbate      cuckoo search algorithm      support vector machine     
Received: 05 July 2017      Published: 05 September 2018
PACS:  TB99  
Fund:the National Natural Science Foundation of China;the National Natural Science Foundation of China
Corresponding Authors: Cai-Yun ZHU     E-mail: tydf15138004018@163.com
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WANG Shu-tao
ZHU Cai-yun
LIU Ming-xin
PENG Tao
CHENG Qi
KONG De-ming
WANG Yu-tian
Cite this article:   
WANG Shu-tao,ZHU Cai-yun,LIU Ming-xin, et al. Study on Fluorescence Spectrometric Detection of Potassium Sorbate Based on CS-SVM[J]. Acta Metrologica Sinica, 2018, 39(5): 747-752.
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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2018.05.29     OR     http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2018/V39/I5/747
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