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...

Full description

Saved in:

Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 36218 - 16
Main Authors:	Longji, Zhu, Zhi, Yang, Jiaqing, Li, Wenhua, Liang, Jingchun, Min
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 16.10.2025 Nature Publishing Group Nature Portfolio
Subjects:	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 Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!