Applicability of machine learning algorithms in predicting chloride diffusion in concrete: Modeling, evaluation, and feature analysis

The resistance to chloride diffusion is one of the most crucial durable properties of concrete. However, traditional methods to evaluate this property are time-consuming and inefficient. In this research, backpropagation-artificial neural network (BP-ANN), support vector regression (SVR), genetic pr...

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Bibliografische Detailangaben

Hauptverfasser:	Weizheng Liu, Guiyong Liu, Xiaolin Zhu
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2024-12-01
Schriftenreihe:	Case Studies in Construction Materials
Schlagworte:	Concrete Durability Machine Learning Algorithm Chloride Diffusion Coefficient Model Evaluation Feature Analysis
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2214509524007241
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