Data Cleaning Based on Multi-sensor Spatiotemporal Correlation
文献类型：会议论文
| 作者 | Shao, Baozhu4; Song CH(宋纯贺)2,3 ; Wang ZF(王忠锋)2,3; Li, Zhexi1; Yu SM(于诗矛)2,3; Zeng P(曾鹏)2,3
|
| 出版日期 | 2019 |
| 会议日期 | August 24-25, 2019 |
| 会议地点 | Nanjing, China |
| 关键词 | Data cleaning Spatiotemporal correlation Sensor networks |
| 页码 | 235-243 |
| 英文摘要 | Sensor-based condition monitoring systems are becoming an important part of modern industry. However, the data collected from sensor nodes are usually unreliable and inaccurate. It is very critical to clean the sensor data before using them to detect actual events occurred in the physical world. Popular data cleaning methods, such as moving average and stacked denoise autoencoder, cannot meet the requirements of accuracy, energy efficiency or computation limitation in many sensor related applications. In this paper, we propose a data cleaning method based on multi-sensor spatiotemporal correlation. Specifically, we find out and repair the abnormal data according to the correlation of sensor data in adjacent time and adjacent space. Real data based simulation shows the effectiveness of our proposed method. |
| 产权排序 | 2 |
| 会议录 | Machine Learning and Intelligent Communications - 4th International Conference, MLICOM 2019, Proceedings
 |
| 会议录出版者 | Springer |
| 会议录出版地 | Berlin |
| 语种 | 英语 |
| ISSN号 | 1867-8211 |
| ISBN号 | 978-3-030-32387-5 |
| 源URL | [http://ir.sia.cn/handle/173321/26023]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 通讯作者 | Song CH(宋纯贺) |
| 作者单位 | 1.Shenyang Power Supply Company, State Grid Liaoning Electric Power Co., Ltd., 110000, Shenyang, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 3.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 4.Liaoning Electric Power Research Institute, State Grid Liaoning Electric Power Co., Ltd., 110000, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Shao, Baozhu,Song CH,Wang ZF,et al. Data Cleaning Based on Multi-sensor Spatiotemporal Correlation[C]. 见:. Nanjing, China. August 24-25, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。