Seismic fragility analysis using nonlinear autoregressive neural networks with exogenous input-Reference-Cited by-同舟云学术

Seismic fragility analysis using nonlinear autoregressive neural networks with exogenous input

Published:2021-03-16 Issue: Volume: Page:1-15
ISSN:1573-2479
Container-title:Structure and Infrastructure Engineering
language:en
Short-container-title:Structure and Infrastructure Engineering

Author:

Sheikh Imran A.¹,Khandel Omid¹^ORCID,Soliman Mohamed¹^ORCID,Haase Jennifer S.²,Jaiswal Priyank³

Affiliation:

1. School of Civil and Environmental Engineering, Oklahoma State University, Stillwater, OK, USA

2. Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA

3. Boone Pickens School of Geology, Oklahoma State University, Stillwater, OK, USA

Funder

Division of Advanced Cyberinfrastructure

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Ocean Engineering,Geotechnical Engineering and Engineering Geology,Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15732479.2021.1894184

Reference63 articles.

1. Seismic denoising using the redundant lifting scheme

2. EVOLVING RBF NEURAL NETWORKS FOR ADAPTIVE SOFT-SENSOR DESIGN

3. null

4. Efficient Analytical Fragility Function Fitting Using Dynamic Structural Analysis

5. Seismic Risk Assessment of Gravity Load Designed Reinforced Concrete Frames Subjected to Mid-America Ground Motions

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