Prediction of bridge deck condition rating based on artificial neural networks

  title={Prediction of bridge deck condition rating based on artificial neural networks},
  author={Tu Trung Nguyen and Kien Dinh},
  journal={Journal of Science and Technology in Civil Engineering (STCE) - NUCE},
  • T. Nguyen, K. Dinh
  • Published 31 August 2019
  • Computer Science
  • Journal of Science and Technology in Civil Engineering (STCE) - NUCE
An accurate prediction of the future condition of structural components is essential for planning the maintenance, repair, and rehabilitation of bridges. As such, this paper presents an application of Artificial Neural Networks (ANN) to predict future deck condition for highway bridges in the State of Alabama, the United States.  A library of 2572 bridges was extracted from the National Bridge Inventory (NBI) database and used for training, validation, and testing the ANN model, which had eight… Expand

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