Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm

doi:10.3390/s17102376

2017-10-18

DOI：10.3390/s17102376

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摘要

En 中文

In this paper, an approach that can fast classify the data from the electronic nose is presented. In this approach the gradient tree boosting algorithm is used to classify the gas data and the experiment results show that the proposed gradient tree boosting algorithm achieved high performance on this classification problem, outperforming other algorithms as comparison. In addition, electronic nose we used only requires a few seconds of data after the gas reaction begins. Therefore, the proposed approach can realize a fast recognition of gas, as it does not need to wait for the gas reaction to reach steady state.

Keyword:

electronic nose

gas sensors

gradient tree boosting

fast recognition

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对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Sensors

IF:

3.5

论文数:

7.2W

被引数:

20.9W

机构

shenzhen university

学者数:

4.6W

论文数: 3.4W

被引数: 72

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