Machine learning-driven feature importance appraisal of seismic parameters on tunnel damage and seismic fragility prediction.
Qi WangPing GengLiangjie WangDingwei HeHuoming ShenPublished in: Eng. Appl. Artif. Intell. (2024)
Keyphrases
- machine learning
- feature importance
- seismic data
- ground motions
- numerical analysis
- prediction accuracy
- maximum likelihood
- random forest
- signal processing
- energy distribution
- feature selection
- natural language processing
- decision trees
- parameter estimation
- machine learning algorithms
- machine learning methods
- pattern recognition
- linear regression model
- information extraction
- root mean square error
- prediction error
- image segmentation
- pairwise
- predictive modeling
- feature set
- semi supervised
- prediction model
- relevance feedback
- high speed