Spatiotemporal dependency data imputation for long-term health monitoring of concrete arch bridges

The structural health monitoring of bridge infrastructures is imperative for ensuring their uninterrupted functionality and mitigating potential hazards. Nevertheless, challenges arise Due to missing data and intricate latent dynamics embedded in field sensing measurements, complicating the forecast...

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Veröffentlicht in:	Scientific reports Jg. 15; H. 1; S. 36218 - 16
Hauptverfasser:	Longji, Zhu, Zhi, Yang, Jiaqing, Li, Wenhua, Liang, Jingchun, Min
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 16.10.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166/986 639/166/988 Algorithms CCF-BiGRU Computer applications Correlation coefficient Cybersecurity Data imputation model Data missing Deep learning Humanities and Social Sciences Missing data multidisciplinary Neural networks Science Science (multidisciplinary) Sensors Structural health monitoring Time series Data missing Data imputation model Structural health monitoring CCF-BiGRU
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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