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Subrat SaurabhAuthor of Kuch Woh PalDr. Saad Shamim Ansari is an Assistant Professor in the Department of Civil Engineering at Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh. He has done B.Tech in Civil Engineering, M.Tech in Structural Engineering, and Ph.D in Civil Engineering from Aligarh Muslim University, focusing on the characterization and structural behavior of concrete using supplementary cementitious materials. His research centers on sustainable cementitious composites, machine learning, and explainable AI applications in civil engineering. He has published several papers in preRead More...
Dr. Saad Shamim Ansari is an Assistant Professor in the Department of Civil Engineering at Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh. He has done B.Tech in Civil Engineering, M.Tech in Structural Engineering, and Ph.D in Civil Engineering from Aligarh Muslim University, focusing on the characterization and structural behavior of concrete using supplementary cementitious materials. His research centers on sustainable cementitious composites, machine learning, and explainable AI applications in civil engineering. He has published several papers in prestigious international journals, including Elsevier, Springer, and ASCE. Also, he has delivered expert lectures at various institutions about the use of machine learning and explainable AI in civil engineering.
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Application of Explainable Artificial Intelligence in Sustainable Construction Materials unveils the cutting-edge integration of machine learning and XAI to revolutionize civil engineering. From predictive modelling of properties in sustainable construction materials to interpreting results using multi-layered, model-agnostic Shapley Additive Explanations (SHAP) techniques, such as summary plots and force plots (primary layer of explainability), and ICE-PDP
Application of Explainable Artificial Intelligence in Sustainable Construction Materials unveils the cutting-edge integration of machine learning and XAI to revolutionize civil engineering. From predictive modelling of properties in sustainable construction materials to interpreting results using multi-layered, model-agnostic Shapley Additive Explanations (SHAP) techniques, such as summary plots and force plots (primary layer of explainability), and ICE-PDP curves (secondary layer of explainability). This book equips readers with the tools to optimise eco-friendly materials while reducing environmental impact.
Perfect for engineers, researchers, and policymakers, it turns complex predictions into practical solutions for a sustainable future.
Application of Explainable Artificial Intelligence in Sustainable Construction Materials unveils the cutting-edge integration of machine learning and XAI to revolutionize civil engineering. From predictive modelling of properties in sustainable construction materials to interpreting results using multi-layered, model-agnostic Shapley Additive Explanations (SHAP) techniques, such as summary plots and force plots (primary layer of explainability), and ICE-PDP
Application of Explainable Artificial Intelligence in Sustainable Construction Materials unveils the cutting-edge integration of machine learning and XAI to revolutionize civil engineering. From predictive modelling of properties in sustainable construction materials to interpreting results using multi-layered, model-agnostic Shapley Additive Explanations (SHAP) techniques, such as summary plots and force plots (primary layer of explainability), and ICE-PDP curves (secondary layer of explainability). This book equips readers with the tools to optimise eco-friendly materials while reducing environmental impact.
Perfect for engineers, researchers, and policymakers, it turns complex predictions into practical solutions for a sustainable future.
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