食品与发酵工业

基于因子分析及BP神经网络的鱼糜挤压膨化产品工艺

  • 张建友 ,
  • 柳敏 ,
  • 王嘉文 ,
  • 林龙 ,
  • 丁玉庭
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网络出版日期: 2014-01-25

Optimization of surimi extrusion product by factor analysis and BP artificial neural network

  • ZHANG Jian-you ,
  • LIU Min ,
  • WANG Jia-wen ,
  • LIN Long ,
  • DING Yu-ting
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Online published: 2014-01-25

摘要

文中对11个鱼糜挤压膨化产品属性指标进行了因子分析。结果表明:前5个公共因子可以解释产品属性的89.732%,各因子贡献率分别为47.220%,16.823%,13.346%,6.775%,5.568%。在此基础上,采用BP人工神经网络模拟操作工艺参数对各因子值的影响,并进行了优化,经优化后的工艺参数为挤压机Ⅲ区加热温度172.0℃、螺杆转速219 r/min、喂料速率8.2 r/min。

本文引用格式

张建友 , 柳敏 , 王嘉文 , 林龙 , 丁玉庭 . 基于因子分析及BP神经网络的鱼糜挤压膨化产品工艺[J]. 食品与发酵工业, 2014 , 40(01) : 124 -129 . DOI: 10.13995/j.cnki.11-1802/ts.2014.01.021

Abstract

Through factor analysis of using the data set of surimi extrusion product properties,the results showed that former 5 components contributed 89.732% to the product and the contribution rate of the 5 components was 47.220%,16.823%,13.346%,6.775% and 5.568% respectively.Subsequently,A BP-ANN model was established in MATLAB to simulate the relationships between running parameters of heating temperature of barrel III,screw speed and feed motor speed with 5 components mentioned above.The optimal running parameters for heating temperature,screw speed and feed motor speed was 172.0 ℃,219r/min,8.2 r/min,respectively.
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