Seismic Damage Rapid Assessment of Road Networks considering Individual Road Damage State and Reliability of Road Networks in Emergency Conditions
Auteur(s): |
Jinlong Liu
Hanxi Jia Junqi Lin Heng Hu |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Advances in Civil Engineering, janvier 2020, v. 2020 |
Page(s): | 1-16 |
DOI: | 10.1155/2020/9631804 |
Abstrait: |
Road networks are one of the vital components of a transportation system that influence the traffic capacity and disaster losses after the earthquakes. The road network reliability is crucial for the postearthquake emergency decision-making. In this study, a method is proposed to assess the seismic damage of road networks considering individual road damage state and reliability of road networks in emergency conditions. First, we assess the importance of the factors that affect seismic road damage using the AdaBoost algorithm. In addition, artificial neural networks are used to evaluate the damage state of an individual road based on the factors that are selected with higher importance. Then, the improved estimation for the reliability of road networks is adopted to assess the damage of road networks. Last, the method is demonstrated using the road networks in Karamay, China. |
Copyright: | © 2020 Jinlong Liu et al. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10429559 - Publié(e) le:
14.08.2020 - Modifié(e) le:
02.06.2021