M. Z. Naser – författare
Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure
1 762 kr
Skickas inom 10-15 vardagar
Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure highlights the growing trend of fostering machine learning to realize contemporary, smart, and safe infrastructure. This volume delves into the latest advancements in machine learning and artificial intelligence, providing readers with practical insights into their applications in the analysis, design, and assessment of civil infrastructure. From the innovative use of Generative Adversarial Networks in the design of shear wall structures to the application of deep learning for damage inspection of concrete structures, each chapter offers a unique perspective on the integration of cutting-edge technology in the field. Explore the potential of AI-driven fire safety design for smart buildings, the challenges and promises of large-scale evacuation modeling, and the use of machine learning classifiers for evaluating liquefaction potential. The book also features an in-depth discussion on explainable machine learning models for predicting the axial capacity of strengthened CFST columns and the development of spalling detection techniques using deep learning. Whether you are a civil engineer, researcher, or industry professional, this book is an invaluable resource that will equip you with the knowledge and tools to revolutionize civil infrastructure design and management. This book presents innovative research results supplemented with case studies from leading researchers in this dynamic and emerging field to be used as benchmarks to carry out future experiments and/or facilitate the development of future experiments and advanced numerical models. The book is delivered as a guide for a wide audience, including senior postgraduate students, academic and industrial researchers, materials scientists, and practicing engineers working in civil, environmental, and mechanical engineering.
Presents the fundamentals of AI/ML and how they can be applied in civil and environmental engineeringShares the latest advances in explainable and interpretable methods for AI/ML in the context of civil and environmental engineeringFocuses on civil and environmental engineering applications (day-to-day and extreme events) and features case studies and examples covering various aspects of applicationsCausal Machine Learning in Civil and Environmental Engineering
Case Studies and Datasets
1 871 kr
Kommande
Machine learning (ML) is in constant transformation and various engineering disciplines are now heavily investing in it too. Currently, the majority of civil- and environmental-based works on ML are utilizing pure data-driven (i.e., black box) models built on correlations and associations. These models, however, do not truly identify the cause-effect relationship needed to answer questions such as: what caused a given structure to fail? Why does a particular construction material behave the way it does under specific conditions?
Causal Machine Learning in Civil and Environmental Engineering: Case Studies and Datasets aims to introduce causal ML approaches to civil and environmental engineering, covering theories, applications, as well as providing datasets, code, and examples of solutions to key problems in the sector. Students, academics, and engineering professionals both in the private and public sectors will find this book to be an invaluable reference source.Introduces causal ML from a civil and environmental engineering perspective, comprehensively covering both theory and step-by-step application proceduresIncludes flowcharts and examples for the successful adoption of causal ML to solve various engineering problemsProvides insight into not only the latest research developments, but also future implications of predictive science for engineeringIs accompanied by a website where all relevant datasets, algorithms, and code are hostedConstruction Materials and Their Properties for Fire Resistance and Insulation
2 236 kr
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Machine Learning for Civil and Environmental Engineers
A Practical Approach to Data-Driven Analysis, Explainability, and Causality
812 kr
Skickas inom 5-8 vardagar
Artificial Intelligence for Resilient Infrastructure and Sustainable Engineering Materials
Proceedings of AIRISE 2025
2 115 kr
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