IRATE
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978-3-030-81718-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
PANEL
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Structural Health Monitoring Based on Data Science Techniques978-3-030-81716-9Series ISSN 2522-560X Series E-ISSN 2522-5618
palette
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Structural Integrityhttp://image.papertrans.cn/s/image/879932.jpg
Discrete
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https://doi.org/10.1007/978-3-030-81716-9Structural Health Monitoring; Structural damage assessment; Data Science; Artificial intelligence techn
Traumatic-Grief
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Alexandre Cury,Diogo Ribeiro,Michael D. ToddPresents a collection of data science applied to structural health monitoring applications.Includes experimental and field examples of detection and identification approaches.Explains how data can be
欲望
发表于 2025-3-26 01:34:11
Applications of Deep Learning in Intelligent Construction,earning in construction safety, such as bolt loosening damage, structural displacement, and worker behavior. Finally, the application scenarios of deep learning in smart construction sites are further discussed.
miscreant
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Irremediable
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白杨鱼
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2522-560X tion and identification approaches.Explains how data can be .The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated
Immunotherapy
发表于 2025-3-26 19:32:20
Book 2022ural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of h