Data mining algorithms for bridge health monitoring: Kohonen clustering and LSTM prediction approaches

In recent years, bridge health monitoring system has been widely used to deal with massive data produced with the continuous growth of monitoring time. However, how to effectively use these data to comprehensively analyze the state of a bridge and provide early warning of bridge structure changes is...

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Vydané v:	The Journal of supercomputing Ročník 76; číslo 2; s. 932 - 947
Hlavní autori:	Guo, Aiping, Jiang, Ajuan, Lin, Jie, Li, Xiaoxiao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.02.2020 Springer Nature B.V
Predmet:	Algorithms Bridges Clustering Compilers Computer Science Data analysis Data mining Deflection Engineering research Interpreters Neural networks Outliers (statistics) Predictions Processor Architectures Programming Languages Structural health monitoring Health monitoring Long short-term memory Kohonen clustering Structural assessment Time series
ISSN:	0920-8542, 1573-0484
On-line prístup:	Získať plný text
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