吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (02): 538-543.

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Optimization of sensor array for identification of corn juice

LIU Jing-jing1, SUN Yong-hai1, DING Jian-feng1, SUN Zhong-lei2   

  1. 1. College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China;
    2. College of Life Science and Technology, Yangtze Normal University, Chongqing 408100, China
  • Received:2012-04-05 Online:2013-03-01 Published:2013-03-01

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Abstract: The sensor array for identification of corn juices was optimized for the key technical issues of automated quality evaluation of corn juices. The inherent relationship among the response signals of sensors was analyzed by the factor analysis, and the sensors of the array were divided into 6 categories according to the correlation coefficients and the component plot in rotated space, and combined into 12 different sets of sensor array. Because the decision boundary surface of the probabilistic neural network can be arbitrary complex, the decision boundary surface built at selected smoothing parameter 0.01 characterizes the impact differences of the data acquired by different sets of sensor array on the identification results. Selecting the sensors named S4,S2,P2,P3,S6 and S7 to build a new sensor array to identify 7 kinds of corn juices. The identification accuracy rate for corn juices by the optimized sensor array was 98.016%, which was higher than 94.444% by the non-optimized one.

Key words: food science and technology, sensor array optimization, probabilistic neural network, factor analysis, identification of corn juice

CLC Number: 

  • TS207.3
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