Temporal Convolution Neural Networks applied to the Electricity Demand Forecast for Malta's grid.
time-series forecasting prediction - electricity forecasting
Machine Learning based Household Electricity Forecasting System using Random Forest Regression. This project predicts electricity consumption using historical power usage, electrical sensor data, and time-based features. Includes a Streamlit web interface for interactive energy forecasting.
Day-ahead electricity price forecasting for the Greek bidding zone (ENTSO-E): leakage-free LightGBM beating naive baselines by 28%, adaptive conformal prediction intervals, and a GitHub Pages dashboard with daily auto-updating forecasts.
LSTM-based electricity consumption monitoring and forecasting system for university campus.
Multi-view clustering for localized global time series forecasting, applied to real-world electricity consumption data using OFMVC, FMVC, K-Means, kShape, and TCN forecasting.
Interactive data visualization and machine learning app for energy consumption analysis and prediction in France, built with Streamlit. (Text in French)
XGBoost-based day-ahead price forecasting pipeline for 21 European electricity bidding zones across the Nordics, Baltics, and Central-West Europe.
Time series forecasting of electricity consumption (15-minute intervals) for single-day prediction
UNIMI Data Science for Economics - Time Series Final Project
Leakage-safe probabilistic forecasting, load-shape clustering, anomaly monitoring, and drift analysis for Türkiye electricity demand.
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