Development and Utilization of Bridge Data of the United States for Predicting Deck Condition Rating Using Random Forest, XGBoost, and Artificial Neural Network
Description:
Article describes how accurately predicting the condition rating of a bridge deck is crucial for effective maintenance and repair planning. This study aims to assess the effectiveness of these algorithms for deck condition rating prediction at the national level.
Date:
January 16, 2024
Creator:
Fard, Fariba & Fard, Fereshteh Sadeghi Naieni