Outlier identify based on BP neural network in dam safety monitoring

Authors:
Ning Li;Peng Li;Xinling Shi;Kai Yan;Wenping Ren
Affiliations:
School of Information Science and Engineering, Yunnan University, Kunming, China;School of Information Science and Engineering, Yunnan University, Kunming, China;School of Information Science and Engineering, Yunnan University, Kunming, China;School of Information Science and Engineering, Yunnan University, Kunming, China;School of Information Science and Engineering, Yunnan University, Kunming, China
Venue:
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
Year:
2010

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Abstract

In popular outlier processing methods, some emphasize on spotted outliers processing and some emphasize on isolated outliers processing. They have seldom processed outliers from the perspective of outlier producing mechanism. This paper aims at the problem of outliers in dam safety monitoring and an outlier identify method which based on BP neural network is presented. This method based on the mechanism of the dam monitoring data formation firstly created the BP neural network predicting model of monitoring data, then identify the outliers. The simulation results indicated that this method works with spotted outliers and isolated outliers and this method has a unique advantage on analysis of the outlier causes.