| Autor: |
Yueai ZHAO, Xingyuan GUO |
| Jazyk: |
English<br />Chinese |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Taiyuan Ligong Daxue xuebao, Vol 52, Iss 6, Pp 907-912 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1007-9432 |
| DOI: |
10.16355/j.cnki.issn1007-9432tyut.2021.06.008 |
| Popis: |
A electrical fire warning algorithm based on multi-source data collaborative sensing was proposed, which takes into account the temporal characteristics of electrical data and the correlation between different sensing data. The relationship between multi-view and low rank analysis is used to identify outliers. Finally, the detection results are fused in real time and effectively to obtain more accurate abnormal data detection results. The experimental results proved the higher anomaly detection rate of the algorithm. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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