Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure 1st Edition
Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure (1st Edition) by M. Z. Naser is a timely guide that brings clarity to complex data-driven engineering challenges. Combining the rigor of structural engineering with modern explainable AI, this book helps professionals turn model outputs into trustworthy actions.
Begin with a concise, practical overview of interpretable machine learning techniques tailored to civil infrastructure — from bridges, roads and tunnels to buildings, dams, and water networks. Clear explanations, real-world examples, and methodical workflows show how interpretability improves design choices, risk assessment, asset management, and regulatory compliance. Readers learn to move beyond “black box” predictions toward transparent, defensible decisions.
Engineers, researchers, infrastructure managers, and policymakers will appreciate the book’s focus on applicability: comparative frameworks, evaluation metrics, and visualization tools that reveal why models make certain recommendations and how to align them with safety, resilience, and lifecycle-cost objectives. Emphasis on cross-regional relevance makes the content valuable for projects across North America, Europe, Asia-Pacific and beyond.
Practical, actionable, and authoritative, this 1st Edition emphasizes reproducible techniques and decision-focused guidance to help you integrate interpretable machine learning into everyday engineering workflows. Whether you’re seeking to improve inspection prioritization, design optimization, or long-term planning, M. Z. Naser equips you to harness AI responsibly and convincingly.
Discover a smarter, clearer approach to machine learning for civil infrastructure. Add this essential resource to your professional library and start making informed, transparent decisions with confidence. Order your copy today.
Note: eBooks do not include supplementary materials such as CDs, access codes, etc.


