@Article{sdhm.2025.069021,
AUTHOR = {Yidong Xu, Weijie Zhuge, Jialei Wang, Xiaopeng Yu, Kan Wu},
TITLE = {Review of the Mechanical Performance Prediction of Concrete Based on Artificial Neural Networks},
JOURNAL = {Structural Durability \& Health Monitoring},
VOLUME = {19},
YEAR = {2025},
NUMBER = {6},
PAGES = {1507--1527},
URL = {http://www.techscience.com/sdhm/v19n6/64506},
ISSN = {1930-2991},
ABSTRACT = {The performance of concrete can be affected by many factors, including the material composition, environmental conditions, and construction methods, and it is challenging to predict the performance evolution accurately. The rise of artificial intelligence provides a way to meet the above challenges. This article elaborates on research overview of artificial neural network (ANN) and its prediction for concrete strength, deformation, and durability. The focus is on the comparative analysis of the prediction accuracy for different types of neural networks. Numerous studies have shown that the prediction accuracy of ANN can meet the standards of the practical engineering applications. To further improve the applicability of ANN in concrete, the model can consider the combination of multiple algorithms and the expansion of data samples. The review can provide new research ideas for development of concrete performance prediction.},
DOI = {10.32604/sdhm.2025.069021}
}