The promise of implementing machine learning in earthquake engineering: A state‐of‐the‐art review
McGill University · Rice University
Abstract
Machine learning (ML) has evolved rapidly over recent years with the promise to substantially alter and enhance the role of data science in a variety of disciplines. Compared with traditional approaches, ML offers advantages to handle complex problems, provide computational efficiency, propagate and treat uncertainties, and facilitate decision making. Also, the maturing of ML has led to significant advances in not only the main‐stream artificial intelligence (AI) research but also other science and engineering fields, such as material science, bioengineering, construction management, and transportation engineering. This study conducts a comprehensive review of the progress and challenges of implementing ML in…
Citation impact
- FWCI
- 32.37
- Percentile
- 100%
- References
- 268
Authors
4Topics & keywords
- Variety (cybernetics)
- Identification (biology)
- Computer science
- Earthquake engineering
- Field (mathematics)
- Categorization
- Engineering
- Resource (disambiguation)