| 光谱学与光谱分析 |
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| A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural Network |
| WANG Shu-tao, CHEN Dong-ying*, WANG Xing-long, WEI Meng, WANG Zhi-fang |
| Institute of Electrical Engineering, Measurement Technology and Instrumentation Key Lab of Hebei Province, Yanshan University, Qinhuangdao 066004, China |
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Abstract In this paper, fluorescence spectra properties of potassium sorbate in aqueous solution and orange juice are studied, and the result shows that in two solution there are many difference in fluorescence spectra of potassium sorbate, but the fluorescence characteristic peak exists in λex/λem=375/490 nm. It can be seen from the two dimensional fluorescence spectra that the relationship between the fluorescence intensity and the concentration of potassium sorbate is very complex, so there is no linear relationship between them. To determine the concentration of potassium sorbate in orange juice, a new method combining Particle Swarm Optimization (PSO) algorithm with Back Propagation (BP) neural network is proposed. The relative error of two predicted concentrations is 1.83% and 1.53% respectively, which indicate that the method is feasible. The PSO-BP neural network can accurately measure the concentration of potassium sorbate in orange juice in the range of 0.1~2.0 g·L-1.
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Received: 2014-10-28
Accepted: 2015-02-04
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Corresponding Authors:
CHEN Dong-ying
E-mail: chendongyingcdy@163.com
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