Structural Health Monitoring Based on Data Science Techniques: 21 - Rilegato

 
9783030817152: Structural Health Monitoring Based on Data Science Techniques: 21

Sinossi

<div><br></div><p>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.</p>

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Dalla quarta di copertina

<div>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.<br></div>

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9783030817183: Structural Health Monitoring Based on Data Science Techniques: 21

Edizione in evidenza

ISBN 10:  3030817180 ISBN 13:  9783030817183
Casa editrice: Springer, 2022
Brossura