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Structural Health Monitoring Based on Data Science Techniques. 2022 ed.
・ISBN 978-3-030-81715-2 hard EUR 149.99
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| 著者・編者 | Cury, Alexandre / Ribeiro, Diogo / Ubertini, Filippo / Todd, Michael D. (eds.), |
|---|---|
| シリーズ | (Structural Integrity) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2021 |
| ページ数 | 484 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-50375＞ |
解説
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 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 how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world.