Neural Network Modelling of Constrained Spatial Interaction Flows



stopped training did not indicate unequivocally the stopping point, and thus, the
determination of
H and δ. This is an issue for further research.

(i) Residuals of the Modular Product Unit Neural Network Model 1Ωsl (x,w)

80

60

-60

-80

(i1) Absolute Residuals (tj -1 ∩sl (x,w)) ; ordered by the size of tj


(i2) Relative Residuals (tj - 1∩sl(x,w)}/ tj ; ordered by the size of tj


(ii) Residuals of the Two-Stage Neural Network Model Approach ΩLonstr ( x,w )

(ii1) Absolute Residuals (tj - ΩLonstr(χ,w)] ; ordered by the size of tj


(ii2) Relative Residuals (tj - ΩLonstr (χ,w)]/ tj ; ordered by the size of tj


(iii)Residuals of the Origin Constrained Gravity Model τ grav


(iii2) Relative Residuals (tj - τg’av (x,w)]/ tj ; ordered by the size of tj

Figure 4: Residuals of the Modular Product Unit Neural Network 1 Ωsl , the Two-
Stage Neural Network Approach
Ω't and the Origin Constrained Gravity
Model Predictions
τ igra
ij


(iii1) Absolute Residuals (tj - τjaa (x,w)) ; ordered by the size of tj


30




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