Application of Graph Convolutional Neural Networks Combined with Single-Model Decision-Making Fusion Neural Networks in Structural Damage Recognition

Application of Graph Convolutional Neural Networks Combined with Single-Model Decision-Making Fusion Neural Networks in Structural Damage Recognition

In cases with a large number of sensors and complex spatial distribution, correctly learning the spatial characteristics of the sensors is vital for structural damage identification. Graph convolutional neural networks (GCNs), unlike other methods, have the ability to learn the spatial characteristi...

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Bibliographic Details
Main Authors: Xiaofei Li, Langxing Xu, Hainan Guo, Lu Yang
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Sensors
Subjects:
graph convolutional neural networks
damage identification
decision-level data fusion
sensor spatial characteristics
model testing
Online Access:https://www.mdpi.com/1424-8220/23/23/9327

Internet

https://www.mdpi.com/1424-8220/23/23/9327

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