CNF Rear Geometry
Vicente Comfort Prediction Model
Transformer-based model predicting denim comfort for any Levi's cut across the Vicente cohort using tension, geometry, and material inputs.
Input Vector
x = [μ_κ, σ_κ, μ_p, σ_p, T_zones, E_seat, E_thigh, θ_yoke, C_rise, M_denim]
- μ_κ = mean curvature, σ_κ = curvature std
- μ_p = mean projection, σ_p = projection std
- T_zones = tension per zone
- E_seat = seat ease, E_thigh = thigh ease
- θ_yoke = yoke angle, C_rise = rise curvature
- M_denim = denim material properties
Comfort Prediction
C_comfort = f(x)
A transformer-based model predicts:
- Comfort score
- Structure score
- Tension risk
- Movement comfort score
- Pose-specific comfort score
Cohort Aggregation
C_cohort = (1/N) · Σ C_comfort^(i)
Aggregated across all cohort members to establish the comfort baseline for Levi's engineering.