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1988•Transportation Research Record Journal of the Transportation Research BoardRequires access

BRIDGE PERFORMANCE PREDICTION MODEL USING THE MARKOV CHAIN

Yi Jiang, Mitsuru Saito, Kumares C. Sinha

Open publisher page 152 citations

Abstract

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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What this paper is about

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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OpenAlex reports 152 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

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.

Key concepts: Bridge (graph theory), Markov chain, Markov model, Reliability engineering, Computer science, Markov process, Engineering, Statistics

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