BRIDGE PERFORMANCE PREDICTION MODEL USING THE MARKOV CHAIN
As part of a study to develop a comprehensive bridge management system for the Indiana Department of Highways (IDOH), a bridge performance prediction model using the Markov chain was developed. The model can be used to predict the percentages of bridges with different condition ratings as well as to develop performance curves of bridges. The Markov chain, a probability-based method, was used in the model to reflect the stochastic nature of bridge conditions. The study exhibited the power of the Markov chain approach in prediction or estimation of future bridge conditions. The procedure, although simple, was found to provide a high level of accuracy in predicting bridge conditions.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/030904720X
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Supplemental Notes:
- This paper appears in Transportation Research Record No. 1180, Bridge Design and Testing. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
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Authors:
- Jiang, Yi
- Saito, Mitsuru
- Sinha, Kumares C
- Publication Date: 1988
Media Info
- Features: Figures; References; Tables;
- Pagination: p. 25-32
- Monograph Title: Bridge design and testing
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Serial:
- Transportation Research Record
- Issue Number: 1180
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Accuracy; Bridge management systems; Bridges; Forecasting; Inspection; Markov chains; Mathematical models; Performance
- Uncontrolled Terms: Bridge condition
- Subject Areas: Bridges and other structures; Design; Highways; I24: Design of Bridges and Retaining Walls;
Filing Info
- Accession Number: 00485572
- Record Type: Publication
- ISBN: 030904720X
- Files: TRIS, TRB, ATRI
- Created Date: Jul 31 1989 12:00AM