MACHINE LEARNING FOR PREDICTING CATALYST EFFICIENCY IN GREEN HYDROGEN PRODUCTION, PREDICTIVE MAINTENANCE, FAULT DETECTION AND MITIGATION
This repository now generates interactive HTML figures alongside static PNGs for publication.
results/Fig1_Feature_Importance.html: Hoverable bar chart of feature impacts.results/Fig3_RUL_Forecast.html: Zoomable degradation forecast with confidence intervals.results/Fig5_LCOH_Analysis.html: Interactive economic pathway analysis.
Open these files in any web browser to explore the data dynamically.
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Install dependencies:
pip install -r code/requirements.txt
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Run the simulation:
python code/main_simulation.py
| Phase | Goal | Deadline | Status |
|---|---|---|---|
| Phase 0 | Setup & Integrity Baseline | Jan 12, 2026 | Active |
| Phase 1 | Data Acquisition & Quantum Sim | Feb 2026 | Pending |
| Phase 2 | Model Training & Validation | Mar 2026 | Pending |
| Phase 3 | Manuscript Refinement | Apr 2026 | Pending |
| Phase 4 | Submission | May 2026 | Pending |
Current Focus (Phase 0):
- Secure Repository & Version Control.
- Audit and Fix References (100% DOI Validity).
- Establish Ethics & Bias Disclosures.
- Baseline KPI Logging.