Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm
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 thi...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-10-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/17/10/2376 |
| _version_ | 1811263338834821120 |
|---|---|
| author | Yuan Luo Wenbin Ye Xiaojin Zhao Xiaofang Pan Yuan Cao |
| author_facet | Yuan Luo Wenbin Ye Xiaojin Zhao Xiaofang Pan Yuan Cao |
| author_sort | Yuan Luo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T19:44:01Z |
| format | Article |
| id | doaj.art-3bdc97b1d237403287a066aafbbdfb32 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:44:01Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-3bdc97b1d237403287a066aafbbdfb322022-12-22T03:19:00ZengMDPI AGSensors1424-82202017-10-011710237610.3390/s17102376s17102376Classification of Data from Electronic Nose Using Gradient Tree Boosting AlgorithmYuan Luo0Wenbin Ye1Xiaojin Zhao2Xiaofang Pan3Yuan Cao4School of Electronic Science and Technology, Shenzhen University, Shenzhen 518060, ChinaSchool of Electronic Science and Technology, Shenzhen University, Shenzhen 518060, ChinaSchool of Electronic Science and Technology, Shenzhen University, Shenzhen 518060, ChinaSchool of Information Engineering, Shenzhen University, Shenzhen 518060, ChinaSchool of Electronic Science and Technology, Shenzhen University, Shenzhen 518060, ChinaIn 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.https://www.mdpi.com/1424-8220/17/10/2376electronic nosegas sensorsgradient tree boostingfast recognition |
| spellingShingle | Yuan Luo Wenbin Ye Xiaojin Zhao Xiaofang Pan Yuan Cao Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm Sensors electronic nose gas sensors gradient tree boosting fast recognition |
| title | Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm |
| title_full | Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm |
| title_fullStr | Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm |
| title_full_unstemmed | Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm |
| title_short | Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm |
| title_sort | classification of data from electronic nose using gradient tree boosting algorithm |
| topic | electronic nose gas sensors gradient tree boosting fast recognition |
| url | https://www.mdpi.com/1424-8220/17/10/2376 |
| work_keys_str_mv | AT yuanluo classificationofdatafromelectronicnoseusinggradienttreeboostingalgorithm AT wenbinye classificationofdatafromelectronicnoseusinggradienttreeboostingalgorithm AT xiaojinzhao classificationofdatafromelectronicnoseusinggradienttreeboostingalgorithm AT xiaofangpan classificationofdatafromelectronicnoseusinggradienttreeboostingalgorithm AT yuancao classificationofdatafromelectronicnoseusinggradienttreeboostingalgorithm |