Infrastructures, Volume 9, Issue 12
2024 December - 29 articles
Cover Story: This study presents a cutting-edge condition rating prediction model utilizing advanced recurrent neural networks (RNNs) with LSTM and GRU architectures enhanced by Time-Distributed layers. Processing time-series inspection data from a state’s National Bridge Inventory, it predicts the Bridge Health Index (BHI) and three component condition ratings. By effectively capturing temporal dependencies and nonlinear dynamics, the model surpasses traditional Markov and machine learning approaches. This innovative approach sets a new benchmark in predictive accuracy for performance assessments, advancing smarter infrastructure management. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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