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data driven methods civil (32 risultati)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems)
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Data Driven Methods For Civil Structural Health Monitoring And Resilience: Latest Developments And Applications
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Aggiungi al carrelloCondizione: New. Mohammad Noori is a professor of mechanical engineering at California Polytechnic State University, San Luis Obispo a fellow and life member of the American Society of Mechanical Engineering (ASME) and a recipient of the Japan Society .
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications (Resilience and Sustainability in . and Manufacturing Engineering Systems)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications
Lingua: Inglese
Editore: Taylor & Francis Ltd Mai 2026, 2026
ISBN 10: 1032308389 ISBN 13: 9781032308388
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.
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Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications (Resilience and Sustainability in . and Manufacturing Engineering Systems)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications (Resilience and Sustainability in . and Manufacturing Engineering Systems)
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Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Paperback)
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032308389 ISBN 13: 9781032308388
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Paperback. Condizione: new. Paperback. Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers. Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides an overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Data Driven Methods for Civil Structural Health Monitoring and Resilience
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Data Driven Methods for Civil Structural Health Monitoring and Resilience
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Paperback)
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032308389 ISBN 13: 9781032308388
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers. Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides an overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Data Driven Methods for Civil Structural Health Monitoring and Resilience (Paperback)
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032308389 ISBN 13: 9781032308388
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers. Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides an overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Data Driven Methods for Civil Structural Health Monitoring and Resilience
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Data Driven Methods for Civil Structural Health Monitoring and Resilience
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers. 358 pp. Englisch.
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Data Driven Methods for Civil Structural Health Monitoring and Resilience
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Mohammad Noori is a professor of Mechanical Engineering at Cal Poly, San Luis Obispo, a Fellow and Life Member of the American Society of Mechanical Engineering and a recipient of the Japan Society for Promotion of Science Fellowship. His work in nonline.
