# Forecourt Prism — Volume Forecast Analytics

> Synthetic forecourt-volume forecasting with weekday-shrunk baselines and missing-data diagnostics. Not EV telemetry, live sales data or streaming analytics.

- Canonical URL: https://mkdata.co.technology/
- Methodology & Equations: https://mkdata.co.technology/methodology/
- Interactive Browser Runtime: https://mkdata.co.technology/run/
- Author & Root Entity: Mohammad Rezwan Khan, PhD (https://mrkhan.co.technology/#person)
- Ecosystem Directory: https://mklab.co.technology/
- Knowledge Graph JSON-LD: https://mkdata.co.technology/knowledge-graph.jsonld

## Governing Mathematical Formulation & Units
- Formula: `b_w = (1 − λ) × mean(V_{d ∈ weekday(w)}) + λ × mean(V_{all}); Backtest MAE = (1/K) Σ_{k=1..K} |V_k − b_{w(k)}|`
- Units: Fuel volume in litres/day (L/day); observation window in days (35 d); backtest window K = 21 days; forecast horizon H = 7 days.

## Reproducible Worked Example
Case 1 (35 observed days, synthetic baseline 600 L/day, zero missing days, 7-day forecast horizon): The weekday-shrunk trailing estimator computes a Daily Baseline of 603.4 L/day with a 21-point held-out Backtest MAE of 62.2 L/day. For 2026-09-05, the point forecast is 557.7 L with heuristic band [448.3 L, 667.0 L].