Gas Network Risk Forecasting

Fri, 01 Nov 2024 00:00:00 +0000

This project was developed for the Hera Group Hackathon, where it earned 2nd place. The task was to detect gas leak risk in a setting dominated by imbalance, sparse events, and operational uncertainty.

The pipeline combines geospatial-temporal feature engineering with synthetic data augmentation through CTGAN and TimeGAN, then uses SHAP to keep the final model interpretable rather than purely predictive.

What I still like about this project is its balance between pragmatism and method: it is a hackathon project, but it already reflects an approach I use often, namely trying to make difficult prediction problems more robust without giving up explainability.

CTGAN | Stefano Blando

Gas Network Risk Forecasting