We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1).
- Authors
Lu, Xinzheng; Burton, Henry
- Abstract
The second part (Part 2) will be published in the very near future and will feature the application of AI and data-driven methods to geotechnical engineering and risk and resilience problems, in addition to more articles on structural analysis and damage evaluation. Described as an automated collapse data constructor (ACDC), the data-augmentation step leverages the understanding of the ground motion properties and their relationship to the structural collapse performance assessment methodology. The rapid development of artificial intelligence (AI) technologies has become foundational to worldwide multidisciplinary research, thereby establishing "AI for science" as a new paradigm. The first four articles in the Part 1 issue examine the application of AI and data-driven methods to ground motion characterization, site classification, and selection and scaling of ground motion records.
- Subjects
EARTHQUAKE resistant design; EARTHQUAKE engineering; DEEP learning; METHODS engineering; MACHINE learning; ARTIFICIAL intelligence; CONVOLUTIONAL neural networks
- Publication
Earthquake Engineering & Structural Dynamics, 2023, Vol 52, Issue 8, p2299
- ISSN
0098-8847
- Publication type
Article
- DOI
10.1002/eqe.3908