Machine learning · ANN & SVR
Energy consumption forecasting
Compare forecasts from an ANN and SVR trained on a generated electricity-demand series.
Interactive simulation · Synthetic data / simulated hardware
Synthetic actual demandANN forecastSVR forecast
Hours 0–167 · training historyHours 168–191 · held-out test
Both models are trained in Python on lagged demand and hour-of-day features. The test set is held out chronologically; each one-hour prediction uses previously observed actual demand. Results shown here belong to this recreation and do not represent the original project.
Forecast comparison
| Test hour | Actual kWh | ANN kWh | SVR kWh |
|---|
Download project source
Includes the browser simulation, implementation notes and supporting example source.