Queue Forecast API Online
ML ensemble forecast of queue levels: 24-hour and 7-day (168h) horizons with confidence bounds. The same model that powers nakordoni.eu predictions.
GET https://nakordoni.eu/api/v1/data/forecast
— quota class: heavy
| Parameter | Description |
|---|---|
ppid | Checkpoint ID, e.g. id_13 (see /api/v1/data/checkpoints) |
prediction_steps | 24 (default) or 168 for 7-day |
Response fields — inside the data object of the envelope. [] marks a list, so data.items[].name is the name field of each element. A field is null, absent or an empty list when we hold no value for it — never a placeholder.
| Field | Description |
|---|---|
data[] | One element per forecast step, nearest first — 24 or 168 of them. |
data[].time | Unix timestamp the step forecasts, with hours_from_now. |
data[].avg_cars | Predicted queue at that hour. |
data[].lower_bound | Confidence band around avg_cars, with upper_bound; the _50 pair is the narrower 50% band. |
data[].type_of_data | Provenance marker of the input reading the step was built from. |
data[].source | Which model produced the step, with formula and the corrected flag when a calibrator adjusted it. |
data[].learned_mult | Per-checkpoint learned multiplier applied, and weather_mult the weather one. |
data[].v4 | Full breakdown from the v4 ensemble — component scores behind avg_cars. |
curl "https://nakordoni.eu/api/v1/data/forecast?ppid=id_13&prediction_steps=24" \ -H "Authorization: Bearer NKD-DEV-XXXX-XXXX-XXXX"
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