DocumentCode
2244719
Title
Outlier identify based on BP neural network in dam safety monitoring
Author
Li, Ning ; Li, Peng ; Xinling Shi ; Yan, Kai ; Ren, Wenping
Author_Institution
Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming, China
Volume
2
fYear
2010
fDate
6-7 March 2010
Firstpage
210
Lastpage
214
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.
Keywords
backpropagation; condition monitoring; dams; geotechnical engineering; neural nets; structural engineering computing; BP neural network predicting model; dam safety monitoring; outlier identify method; outlier processing methods; Additive noise; Labeling; MIMO; Monitoring; Neural networks; Rayleigh channels; Receiving antennas; Safety; Transmitters; Transmitting antennas; BP neural network; dam safety monitoring; outlier identifying; prediction model;
fLanguage
English
Publisher
ieee
Conference_Titel
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location
Wuhan
ISSN
1948-3414
Print_ISBN
978-1-4244-5192-0
Electronic_ISBN
1948-3414
Type
conf
DOI
10.1109/CAR.2010.5456564
Filename
5456564
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