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Springer Structural Health Monitoring and Data Science Book

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Description

Explore the intersection of structural health monitoring (SHM) and advanced data science in this technical volume from Springer. As big data availability grows, the ability to transform real-time data acquisition into actionable decisions regarding structural performance and maintenance becomes essential. This book addresses the rapid advancement of SHM through machine learning and data analytics techniques. Designed to bridge the gap between research and practice, the text presents a representative collection of data science applications used to assess structural health, maintenance needs, and life cycle assessments. It is an essential resource for understanding how modern data-driven methods improve the execution of structural integrity monitoring in real-world scenarios.

Key Features

Published by Springer as part of the Structural Integrity series for professional and academic use.

Covers the transformation of real-time data acquisition into actionable decisions for structural performance.

Explores how big data availability and advanced data science accelerate modern SHM paradigms.

Examines machine learning and data analytics techniques used to advance structural health monitoring.

Provides a representative collection of data science applications for structural health and life cycle assessment.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
25 October 2022
Listed Since
28 September 2022

Barcode

No barcode data available

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