Adaptive Blend Engine

India / Telangana / Hyderabad · Weight allocation

Which model should we trust right now?

Adaptive Blend Engine

The system decides how much to trust each model for this exact forecast — and shows its reasoning.

Pre-seeded contexts

Location

Hyderabad, Telangana

Season

Southwest Monsoon

Regime

Heavy rainfall

Lead time

24h

Variable

Rainfall

Weight allocation

Click a source to see why it earned that weight.

Weights current

Weights reflect recent historical skill for the selected context, with a 5% floor per source.

Why 31% for BharatFS?

Deterministic composite of five skill factors.

Recent skillgood
Regional skillhigh
Regime skillgood
Lead-time skillhigh
Recent stabilitygood
Composite skill score0.80

Adaptive blend ready

Hyderabad · +24h

0mm

Expected range

34–51 mm

Confidence

87%

vs best model

+12.4%

vs simple average

+16.8%

Forecast composition

Source value and its share of the blend.

  • BharatFS31.2 mm31%
  • NCUM40.7 mm27%
  • GFS32 mm14%
  • GEFS44.3 mm20%
  • AI Forecast Proxy50.3 mm8%

Blending formula

Transparent, inspectable, deterministic.

Blended forecast

Σ ( model forecast × adaptive model weight )

Running the blend replays the real computation order on deterministic demo data; values do not change between runs for the same context.