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WO3 sensors array coupled with pattern recognition method for gases identification

机译:WO3传感器阵列结合模式识别方法进行气体识别

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This paper presents the performance of gas sensors as electronic nose coupled with pattern recognition method for gases identification. In fact, the implementation of the electronic nose in a characterization process is based on two fundamental phases: a learning phase and a phase of identification. That is why we need an accurate extraction method in order to obtain performant classification. In this study, we propose to extract transient parameters in a dynamic mode: derivate and integral. The performance of these features is validated by the analysis method: principal component analysis (PCA) and K nearest neighbors (KNN), which present 98, 74% rate classification.
机译:本文介绍了气体传感器作为电子鼻结合模式识别方法进行气体识别的性能。实际上,在表征过程中电子鼻的实现基于两个基本阶段:学习阶段和识别阶段。这就是为什么我们需要一种精确的提取方法以获得性能分类的原因。在这项研究中,我们建议以动态模式提取瞬态参数:微分和积分。这些功能的性能已通过以下分析方法进行了验证:主成分分析(PCA)和K最近邻(KNN),它们显示了98、74%的费率分类。

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