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Ensemble Machine Learning for Seismic PGA Prediction

Based on: "Ensemble machine learning models for predictive analysis: Application to seismic ground motion data"[cite: 12].

Results [cite: 166, 202, 220]

  • Random Forest: R² = 0.8573
  • Gradient Boosting: R² = 0.857
  • Stacked (Meta: LR): R² = 0.868

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Official implementation of "Ensemble machine learning models for predictive analysis: Application to seismic ground motion data" A novel framework for predicting PGA using the NGA-West2 database.

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