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Data Mining in Structural Dynamic Analysis

Overview of attention for book
Cover of 'Data Mining in Structural Dynamic Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Damage Detection for Structural Health Monitoring of Bridges as a Knowledge Discovery in Databases Process
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    Chapter 2 Structural Health Monitoring of Periodic Infrastructure: A Review and Discussion
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    Chapter 3 Railway Wheel Out-of-Roundness and Its Effects on Vehicle–Track Dynamics: A Review
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    Chapter 4 Dynamic Response Analysis of Wind Turbines Under Long-Period Ground Motions
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    Chapter 5 Intelligent Image Analysis Technology and Application for Rail Track Inspection
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    Chapter 6 Investigation on the Effect of High-Frequency Torsional Impacts on the Torsional Vibration of an Oilwell Drill String in Slip Phase
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    Chapter 7 Carriage–Rail–Viaduct Coupling Analysis Using Dynamic Flexibility Method
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    Chapter 8 Dynamic Response Reconstruction to Supplement the Data Insufficiency
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    Chapter 9 A Proposed Method for the Use of the IBIS-FS in Experimental Modal Analysis of Buildings
Attention for Chapter 1: Damage Detection for Structural Health Monitoring of Bridges as a Knowledge Discovery in Databases Process
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Citations

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4 Mendeley
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Chapter title
Damage Detection for Structural Health Monitoring of Bridges as a Knowledge Discovery in Databases Process
Chapter number 1
Book title
Data Mining in Structural Dynamic Analysis
Published by
Springer, Singapore, January 2019
DOI 10.1007/978-981-15-0501-0_1
Book ISBNs
978-9-81-150500-3, 978-9-81-150501-0
Authors

Moisés Silva, Adam Santos, Elói Figueiredo

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Student > Master 1 25%
Unknown 1 25%
Readers by discipline Count As %
Engineering 1 25%
Unknown 3 75%

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