Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 1 of 1
Full-Text Articles in Engineering
Assessing Key Factors Influencing Fire-Induced Spalling Of Concrete Using Explainable Artificial Intelligence (Xai), Mohammad Khaled Gazi Albashiti
Assessing Key Factors Influencing Fire-Induced Spalling Of Concrete Using Explainable Artificial Intelligence (Xai), Mohammad Khaled Gazi Albashiti
All Theses
This thesis adopts eXplainable Artificial Intelligence (XAI) to identify the key factors influencing the fire-induced spalling of concrete and to extract new insights into the fire-induced spalling phenomenon. In this pursuit, an XAI model was developed, validated, and then augmented with two explainability measures, namely, Shapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). The proposed XAI model not only can predict the fire-induced spalling with high accuracy (i.e., >92 %) but can also articulate the reasoning behind its predictions (as in, the proposed model can specify the rationale for each prediction instance); thus, providing us with valuable insights …