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基于主成分分析、神经网络对啤酒感官评价的预测
引用本文:钟成,黄奕雯,贾士儒,董建军,郝俊光,李清亮.基于主成分分析、神经网络对啤酒感官评价的预测[J].食品与发酵工业,2013,39(3):48-51.
作者姓名:钟成  黄奕雯  贾士儒  董建军  郝俊光  李清亮
作者单位:1. 啤酒生物发酵工程国家重点实验室(筹),山东青岛,266061;工业发酵微生物教育部重点实验室,天津科技大学,天津,300457
2. 工业发酵微生物教育部重点实验室,天津科技大学,天津,300457
3. 啤酒生物发酵工程国家重点实验室(筹),山东青岛,266061
基金项目:国家重点基础研究发展(973)计划(No.2010CB735706)资助及啤酒生物发酵工程国家重点实验室开放基金
摘    要:该研究运用主成分分析(PCA)结合误差反向传播(BP)神经网络对啤酒感官评价进行了预测。把啤酒中11种理化及风味指标进行主成分分析,以除去数据之间的线性相关性,提取后的理化及风味指标做为输入数据,感官评价得分作为输出数据,运用BP神经网络建立啤酒感官评价预测的模型。使用此模型对50种啤酒的感官得分进行预测,预测最大相对误差为2.68%。结果表明,主成分分析和神经网络相结合的这种方法能够准确预测啤酒感官评价得分。

关 键 词:风味物质  主成分分析  BP神经网络  啤酒感官评价

Estimation of beer sensory evaluation based on principal component analysis and neural network
Zhong Chen,Huang Yi-wen,Jia Shiru,Dong Jian-jun,Hao Jun-guang,Li Qing-liang.Estimation of beer sensory evaluation based on principal component analysis and neural network[J].Food and Fermentation Industries,2013,39(3):48-51.
Authors:Zhong Chen  Huang Yi-wen  Jia Shiru  Dong Jian-jun  Hao Jun-guang  Li Qing-liang
Affiliation:1,2 1(State Key Laboratory of Biological Fermentation Engineering of Beer(in preparation),Qingdao 266061,China) 2(Key Laboratory of Industrial Fermentation Microbiology,Tianjin University of Science and Technology,Tianjin 300457,China)
Abstract:The method integrating principal component analysis(PCA) with back propagation(BP) neural networks was applied to predict the beer sensory evaluation.A total of 11 physicochemical indexes was extracted by PCA to eliminate linear relevance and then used as input.Sensory evaluation scores were used as output.BP neural network was established to model the beer sensory evaluation.Finally,sensory evaluation scores of 50 beers were predicted by this model.The experimental results showed that the maximum predictive relative error was 2.68%,suggesting that the methods integrating PCA with BP networks could precisely predict the beer sensory evaluation.
Keywords:flavor component  principal component analysis  back propagation neural network  beer sensory evaluation
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