5forecast time scales: hour / day / week / month / year
4missing-value strategies
4exports: CSV / HTML / TXT / ZIP
3cached artifacts per model configuration
These are repository-verifiable system capabilities, not cherry-picked model benchmark numbers.
02 / Architecture
Buoy Datastation, time, marine observations
Pipelineresample, missing data, smoothing, QA
LSTM2× LSTM + Dropout + Dense(1)
ProductRMSE / R / risk / downloads
03 / Risk & validation
Wave thresholdWarning 2.5, danger 4.0 for significant wave height.Wind thresholdWarning 10.0, danger 17.0 for wind speed.ValidationTemporal train/validation split with RMSE, correlation R and epsilon hit rate.CacheConfiguration hash reuses the Keras model, scaler and training history.
04 / Runtime UI
The original app.py was started in GitHub Actions and captured with Chromium using a minimal fixture dataset.
