• Title/Summary/Keyword: post-earthquake retrofit

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Artificial Intelligence Estimation of Network Flows for Seismic Risk Analysis (지진 위험도 분석에서 인공지능모형을 이용한 네트워크 교통량의 예측)

  • Kim, Geun-Young
    • Journal of Korean Society of Transportation
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    • v.17 no.3
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    • pp.117-130
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    • 1999
  • Earthquakes damage roadway bridges and structures, resulting in significant impacts on transportation system Performance and regional economy. Seismic risk analysis (SRA) procedures establish retrofit priorities for vulnerable highway bridges. SRA procedures use average daily traffic volumes to determine the relative importance of a bridge. This research develops a cost-effective transportation network analysis (TAN) procedure for evaluating numerous traffic flow analyses in terms of the additional system cost due to failure. An important feature of the TNA Procedure is the use of an associative memory (AM) approach in the artificial intelligence held. A simple seven-zone network is developed and used to evaluate the TNA procedure. A subset of link failure system states is randomly selected to simulate synthetic post-earthquake network flows. The performance of different AM model is evaluated. Results from numerous link-failure scenarios demonstrate the applicability of the AM models to traffic flow estimation.

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