Intensity Prediction Model Based on Machine Learning for Regional Earthquake Early Warning-Reference-Cited by-同舟云学术

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Intensity Prediction Model Based on Machine Learning for Regional Earthquake Early Warning

Published:2024-04-01 Issue:7 Volume:24 Page:10491-10503
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Zhang Kaiwen¹^ORCID,Lozano-Galant Fidel²,Xia Ye³^ORCID,Matos Jose⁴

Affiliation:

1. Department of Bridge Engineering, Tongji University, Shanghai, China

2. Department of Civil and Building Engineering, University of Castilla-La Mancha, Ciudad Real, Spain

3. Shanghai Qizhi Institute and the Department of Bridge Engineering, Tongji University, Shanghai, China

4. Department of Civil and Environmental Engineering, University of Minho, Braga, Portugal

Funder

National Natural Science Foundation of China

Project to Attract Foreign Experts

Technology Cooperation Project of Shanghai Qizhi Institute Cooperation

Top Discipline Plan of Shanghai Universities-Class I

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10487994/10413337.pdf?arnumber=10413337

Reference52 articles.

1. Real-time seismology and earthquake hazard mitigation

2. The ElarmS Earthquake Early Warning Methodology and Application across California

3. A deep neural network framework for real‐time on‐site estimation of acceleration response spectra of seismic ground motions

4. Seismic fragility assessment and maintenance management on regional bridges using bayesian multi-parameter estimation

5. Hysteretic parameters identification of RC frame structure with Takeda model based on modified CKF method

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