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scipy-optimize

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sambo

An industrial digital twin solution for Combined Cycle Power Plants (CCPP). This project leverages XGBoost machine learning models and mathematical optimization (SLSQP) to predict net electrical output and prescribe the optimal exhaust vacuum setpoint, maximizing thermal efficiency based on real-time environmental conditions.

  • Updated Jun 24, 2026
  • Jupyter Notebook

Resource-efficient rank-based ensembling for Kaggle S6E9. A lightweight solution optimizing ensemble weights via mathematical ranking intuition instead of brute-force compute. Focuses on feature interactions and synthetic data artifact correction built via AI-assisted workflows.

  • Updated Sep 19, 2026
  • Jupyter Notebook

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