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Special Issue Submission Invitation About Shock and Vibration

2018-10-16

Shock and Vibration (pdf)

Machine Learning Techniques for Structural Health Monitoring

In recent years, there is an increased need for early detection of structural faults or damage, what has been referred as structural health monitoring (SHM). Structural health monitoring involves the use of a sensor network to collect data from the monitored structure. The amount of data collected from a given structure is often complex and large. Thus, data analytics has become an important process to extract valuable information from the measurements for decision making with respect to diagnosis of the structural condition and the prognosis of structural damage.

This special issue is aimed to exploit the advances in applying Machine Learning Techniques for Structural Health Monitoring. We invite researchers to contribute with original research articles that include new theoretical approaches, numerical simulations or experimental studies of applying Advanced Signal Processing and Computational Intelligence Techniques for Structural Health Monitoring. We also welcome review articles summarizing the current state of the art.

 

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Current Issue

Vol 2 No 3 (2018): Theoretical and Applied Engineering

Table of Contents

Agronomy 

NEURONAL NETWORKS TO DESCRIBE EPIDEMICS OF COCOA WITCHES’ BROOM

Edson Ampélio Pozza, Luiz Antônio Maffia, Carlos Arthur Barbosa da Silva, Marcelo de Carvalho Alves, José Luis Braga, João de Cássia do Bonfim Costa

Published: 2018-10-15

Articles

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