| 基于PSO-SVM的白酒品质鉴别电子鼻 |
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| 引用本文： | 蒋鼎国,周红标,耿忠华. 基于PSO-SVM的白酒品质鉴别电子鼻[J]. 中国酿造, 2011, 0(11) |
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| 作者姓名： | 蒋鼎国 周红标 耿忠华 |
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| 作者单位： | 1. 淮阴工学院科技处,江苏淮安,223003
2. 淮阴工学院电子与电气工程学院,江苏淮安,223003 |
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| 基金项目： | 江苏省高校自然科学基金资助项目，江苏省教育厅成果转化项目(Jh10-49):淮安市科技支撑项目(SN1045):淮阴工学院科技项目 |
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| 摘 要： | 研制一套白酒品质识别电子鼻,对检测样品的气味数据进行预处理,提取稳态响应值,并作为支持向量机(support vector mchine,SVM)分类模型的输入.为提高识别的准确度,利用粒子群算法(particle swarm optimization,PSO)来优化SVM的参数c和g.不同品质的白酒所对应的电子鼻传感器响应特性不同,PSO- SVM分类模型的识别准确率达到了97.5％.结果证明基于PSO-SVM分类模型具有较强的学习能力和泛化能力,可用于白酒品质鉴别电子鼻.
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| 关 键 词： | 白酒识别 电子鼻 支持向量机 粒子群算法 |
Liquor recognition electronic nose based on PSO-SVM |
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| JIANG Dingguo,ZHOU Hongbiao,GENG Zhonghua. Liquor recognition electronic nose based on PSO-SVM[J]. China Brewing, 2011, 0(11) |
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| Authors: | JIANG Dingguo ZHOU Hongbiao GENG Zhonghua |
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| Affiliation: | JIANG Dingguo1,ZHOU Hongbiao2,GENG Zhonghua2(1.Department of Science and Technology,Huaiyin Institute of Technology,Huaiyin 223003,China,2.Faculty of Electronic and Electrical Engineering,Huaiyin Institute of Techology,China) |
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| Abstract: | In this paper,the classification model of support vector machine(SVM) for liquors was established.To improve the accuracy of typical samples,the modeling parameters c and g for SVM were optimized by particle swarm optimization(PSO).The simulative results indicated that the classification accuracy of four kinds of liquors samples which were acquired by electronic nose reached 97.5% based on PSO-SVM.The liquors recognition electronic nose had different characteristic response signals for them,which could reco... |
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| Keywords: | liquor recognition electronic nose support vector machine particle swarm optimization |
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