Impact load identification method based on artificial neural network for submerged floating tunnel under collision-Reference-Cited by-同舟云学术

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Impact load identification method based on artificial neural network for submerged floating tunnel under collision

Published:2023-10 Issue: Volume:286 Page:115641
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Baek Seung-Min,Park Jae-Chan,Jung Hyung-Jo

Funder

Ministry of Science, ICT and Future Planning

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Ocean Engineering,Environmental Engineering

Reference25 articles.

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2. Application of artificial neural networks to load identification;Cao;Comput. Struct.,1998

3. Diagnosis of reinforced concrete structural damage based on displacement time history using the back-propagation neural network technique;Chung-Huei;J. Comput. Civ. Eng.,2002

4. Levenberg–Marquardt iterative regularization for the pulse-type impact-force reconstruction;Gunawan;J. Sound Vib.,2012

5. Mooring System Integrity: Deteriorative Mechanisms on Mooring Systems and Appropriate Inspection Techniques;Hall,2011

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1. Research progress and prospects on pier-type submerged floating tunnels;Ocean Engineering;2024-09

2. Deep recurrent-convolutional neural network learning and physics Kalman filtering comparison in dynamic load identification;Structural Health Monitoring;2024-07-27

3. Identification of Wind Load Exerted on the Jacket Wind Turbines from Optimally Placed Strain Gauges Using C-Optimal Design and Mathematical Model Reduction;Journal of Marine Science and Engineering;2024-03-27

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