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- W2808659301 abstract "针对基于神经网络的多气体定性识别方法中存在的过学习和泛化能力差的问题,提出了一种基于支持向量机(SVM)与多传感器数据融合的多气体定性识别方法.该方法采用结构化风险最小化准则的多类分类支持向量机对由多个气体传感器、温度和湿度传感器组成的传感阵列的数据进行融合,克服了传统方法的缺陷,消除了环境温度与湿度等因素的影响.实现了100%的定性识别率,实验结果证明了该方法的有效性." @default.
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- W2808659301 date "2009-01-01" @default.
- W2808659301 modified "2023-09-24" @default.
- W2808659301 title "Multi-gases qualitative identification using SVM and data fusion" @default.
- W2808659301 hasPublicationYear "2009" @default.
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