Master's Dissertation: Unsupervised Low-Frequency NILM for Industrial Loads
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Updated
Feb 13, 2024 - MATLAB
Master's Dissertation: Unsupervised Low-Frequency NILM for Industrial Loads
A rules‑driven trading framework designed to identify high‑strength stocks within broadly healthy market conditions, executing at most one trade per week when its criteria are met. It operates as a low‑frequency, systematic trend‑following swing strategy—a modern hybrid of classic Turtle‑style principles—leveraging the Trading 212 API for portfolio
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