Chapter
Apr 26, 2012
Automated Procedures for Improving the Accuracy of Sensor-Based Monitoring Data
Authors: Rebecca B. Buchheit [email protected], James H. Garrett, Jr. [email protected], Sue McNeil [email protected], and Margaret H. ChalklineAuthor Affiliations
Publication: Applications of Advanced Technologies in Transportation (2002)
Abstract
In this paper, we describe an automated method for detecting and correcting outliers in a data set generated by a weigh-in-motion scale. We use clustering and regression to identify outliers in an aggregated version of the data set. Then we compare the attribute distributions of outliers and the distributions of normal data to identify the mechanisms that cause the outliers. After we remediated these mechanisms, the outlier data closely resembled the normal data.
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Published In
Applications of Advanced Technologies in Transportation (2002)
Pages: 402 - 409
Copyright
© 2002 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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Affiliations
Doctoral Candidate, Dept of Civil and Env Eng, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213. E-mail: [email protected]
Professor, Dept of Civil and Env Eng, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213. E-mail: [email protected]
Director, Urban Transportation Center, University of Illinois at Chicago. E-mail: [email protected]
Margaret H. Chalkline
Engineer, Minnesota Department of Transportation
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.