Zhishen Wu
According to our database1,
Zhishen Wu
authored at least 20 papers
between 2004 and 2023.
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Bibliography
2023
A deep-learning approach for predicting water absorption in composite pipes by extracting the material's dielectric features.
Eng. Appl. Artif. Intell., May, 2023
Structural Health Monitoring of Composite Pipelines Utilizing Fiber Optic Sensors and an AI-Based Algorithm - A Comprehensive Numerical Study.
Sensors, 2023
2022
Long-Short Term Memory Network-Based Monitoring Data Anomaly Detection of a Long-Span Suspension Bridge.
Sensors, 2022
2021
A journal with quality standards unmatched by any other journal in the field of civil engineering.
Comput. Aided Civ. Infrastructure Eng., 2021
2019
Erratum: Cheng, Y.; Zhao, C.; Zhang, J.; Wu, Z. Application of a Novel Long-Gauge Fiber Bragg Grating Sensor for Corrosion Detection via a Two-Level Strategy. <i>Sensors</i> 2019, <i>19</i>, 954.
Sensors, 2019
Application of a Novel Long-Gauge Fiber Bragg Grating Sensor for Corrosion Detection via a Two-level Strategy.
Sensors, 2019
2016
Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure.
Sensors, 2016
Stripe-PZT Sensor-Based Baseline-Free Crack Diagnosis in a Structure with a Welded Stiffener.
Sensors, 2016
2015
2013
2012
2011
Vibration-Based Damage Localization in Flexural Structures Using Normalized Modal Macrostrain Techniques from Limited Measurements.
Comput. Aided Civ. Infrastructure Eng., 2011
2009
Modelling of time-dependent bonding and debonding in structures externally strengthened with fibre reinforced polymer sheets.
Int. J. Model. Identif. Control., 2009
Failure Mechanism of Deformed Concrete Tunnels Subject to Diagonally Concentrated Loads.
Comput. Aided Civ. Infrastructure Eng., 2009
2008
A Model-free Method for Damage Locating and Quantifying in a Beam-like Structure Based on Dynamic Distributed Strain Measurements.
Comput. Aided Civ. Infrastructure Eng., 2008
2007
Comput. Aided Civ. Infrastructure Eng., 2007
2006
2004
Direct identification of structural parameters from dynamic responses with neural networks.
Eng. Appl. Artif. Intell., 2004