Interpretable Machine Learning for Prediction of Post-Fire Self-Healing of Concrete

Interpretable Machine Learning for Prediction of Post-Fire Self-Healing of Concrete

Developing accurate and interpretable models to forecast concrete’s self-healing behavior is of interest to material engineers, scientists, and civil engineering contractors. Machine learning (ML) and artificial intelligence are powerful tools that allow constructing high-precision predictions, yet...

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Bibliographic Details
Main Authors: Magdalena Rajczakowska, Maciej Szeląg, Karin Habermehl-Cwirzen, Hans Hedlund, Andrzej Cwirzen
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Materials
Subjects:
autogenous self-healing
cementitious materials
high temperature
artificial neural network
ensemble methods
mechanical properties
Online Access:https://www.mdpi.com/1996-1944/16/3/1273

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https://www.mdpi.com/1996-1944/16/3/1273

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