Rapid identification method for on-road high-emission vehicle based on deep semi-supervised anomaly detection
文献类型：期刊论文
| 作者 | Han, Lingran1,2; Zhang, Yujun1 ; He, Ying1; You, Kun1; Liu, Wenqing1; Xie, Hao1
|
| 刊名 | MEASUREMENT
 |
| 出版日期 | 2025-01-15 |
| 卷号 | 239 |
| 关键词 | High-emission vehicle identification Data fusion Deep anomaly detection Semi-supervised learning The chassis and engine dynamometer testing On-road remote sensing system |
| ISSN号 | 0263-2241 |
| DOI | 10.1016/j.measurement.2024.115430 |
| 通讯作者 | Xie, Hao(hxie@aiofm.ac.cn) |
| 英文摘要 | This study aims to identify high-emission vehicles in urban traffic management. Existing high-emission vehicle identification models typically overlook the dispersed anomaly data distribution, and machine learning anomaly detection methods face difficulties in learning decision boundaries, leading to reduced detection performance. To address these issues, this study proposes a semi-supervised learning method based on data fusion and deep anomaly detection. This method integrates the chassis and engine dynamometer test data with on-road remote sensing system data to obtain more comprehensive vehicle emission information. Experimental results demonstrate that the proposed method introduces a penalty mechanism for anomaly samples, encouraging the model to increase the dissimilarity in similarity between normal and abnormal data at the latent data distribution level. In vehicle emission datasets from different regions, this method achieves over 95% AUC, demonstrating strong applicability and accuracy. |
| 资助项目 | National Natural Science Foundation of China[62033012] ; China Postdoctoral Science Foundation[2023M733541] ; Youth Fund of Hefei Institutes of Physical Science[YZJJ2024QN12] ; National Key Research and Development Program of China[2023YFC3705300] |
| WOS研究方向 | Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:001295628900001 |
| 出版者 | ELSEVIER SCI LTD |
| 资助机构 | National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Youth Fund of Hefei Institutes of Physical Science ; National Key Research and Development Program of China |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/136052]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Xie, Hao |
| 作者单位 | 1.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Peoples R China |
| 推荐引用方式 GB/T 7714 | Han, Lingran,Zhang, Yujun,He, Ying,et al. Rapid identification method for on-road high-emission vehicle based on deep semi-supervised anomaly detection[J]. MEASUREMENT,2025,239. |
| APA | Han, Lingran,Zhang, Yujun,He, Ying,You, Kun,Liu, Wenqing,&Xie, Hao.(2025).Rapid identification method for on-road high-emission vehicle based on deep semi-supervised anomaly detection.MEASUREMENT,239. |
| MLA | Han, Lingran,et al."Rapid identification method for on-road high-emission vehicle based on deep semi-supervised anomaly detection".MEASUREMENT 239(2025). |
入库方式： OAI收割
来源：合肥物质科学研究院
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