| 한글제목(Korean Title) |
무선 센서 네트워크에서 장애 검출을 위한 결합 주성분분석과 적응형 임계값 |
| 영문제목(English Title) |
Joint PCA and Adaptive Threshold for Fault Detection in Wireless Sensor Networks |
| 저자(Author) |
Thien-Binh Dang
Vi Van Vo
Duc-Tai Le
Moonseong Kim
Hyunseung Choo
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| 원문수록처(Citation) |
VOL 27 NO. 01 PP. 0069 ~ 0071 (2020. 05) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Principal Component Analysis (PCA) is an effective data analysis technique which is commonly uused for fault detection on collected data of Wireless Sensor Networks (WSN). However, applying PCA on the whole data make the detection performance low.In this paper, we propose Joint PCA and Adaptive Threshold for Fault Detection (JPATAD). Experimental results on a real dataset show a remarkably higher performance of JPATAD comparing to conventional PCA model in detection of noise which is a popular fault in collected data of sensors.
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| 키워드(Keyword) |
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| 파일첨부 |
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