J
Jong Wan Hu
Researcher at Incheon National University
Publications - 196
Citations - 2143
Jong Wan Hu is an academic researcher from Incheon National University. The author has contributed to research in topics: Engineering & Damper. The author has an hindex of 20, co-authored 154 publications receiving 1378 citations. Previous affiliations of Jong Wan Hu include Hanyang University & Georgia Institute of Technology.
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Novel Predictive Model of the Debonding Strength for Masonry Members Retrofitted with FRP
TL;DR: In this article, gene expression programming (GEP) has been used to predict the debonding strength of retrofitted masonry members, and the results indicate that the new model has the best efficiency among the models examined and represents an improvement to other models.
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Structural Performance Assessment Based on Statistical and Wavelet Analysis of Acceleration Measurements of a Building during an Earthquake
TL;DR: In this article, the analysis of structural health monitoring (SHM) system based on acceleration measurements during an earthquake was introduced, which indicated that the acceleration, displacement, and torsional responses of the roof recording point on the top floor of the building are more dominant in the X direction.
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Safety and Reliability Evaluations of Bridge Behaviors under Ambient Truck Loads through Structural Health Monitoring and Identification Model Approaches
Firouzjahi, Hassan,Mosbeh R. Kaloop,Mosbeh R. Kaloop,Mohammed El-Diasty,Mohammed El-Diasty,Jong Wan Hu +5 more
TL;DR: This research investigates the use of output-only structural health monitoring (SHM) to evaluate the reliability and safety of highway steel plate girders of WonHyo bridge and shows the effectiveness of PARIMA for detecting structures damages and analyzing structure’s reliability in semi-static and dynamic domains.
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Real-time prediction of water level change using adaptive neuro-fuzzy inference system
TL;DR: In this paper, the least squares-based harmonic analysis method was used for water level prediction in a maritime application, and water prediction is traditionally developed using the least square based harmonic analysis.
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Optimizing the De-Noise Neural Network Model for GPS Time-Series Monitoring of Structures
Mosbeh R. Kaloop,Jong Wan Hu +1 more
TL;DR: Results show that the Adaptive neural networks filter is suggested for de-noising the observations, specifically for the GPS displacement components of structures, and is expected to have significant influence on the design of structures in the low frequency responses and measurements’ contents.