| 书目名称 | Structural Health Monitoring Based on Data Science Techniques |
| 编辑 | Alexandre Cury,Diogo Ribeiro,Michael D. Todd |
| 视频video | |
| 概述 | Presents 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 |
| 丛书名称 | Structural Integrity |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2022 |
| 关键词 | Structural Health Monitoring; Structural damage assessment; Data Science; Artificial intelligence techn |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-81716-9 |
| isbn_softcover | 978-3-030-81718-3 |
| isbn_ebook | 978-3-030-81716-9Series ISSN 2522-560X Series E-ISSN 2522-5618 |
| issn_series | 2522-560X |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 19:28:38
