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ON THE INVERSE POINT-SOURCE PROBLEM OF THE POISSON EQUATION

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Fig. 1.  Geometry of the heat conduction  problem; θ i  represent the pointwise boundary  temperature measurements  point source at +  (xo, yo)   _    θ ENθ| Wθ        _ | Sθ x y 10 1  0T∞=T(x,y)
Fig. 2. a)  Point sources picked from  uniform  probability density on a square.
Fig. 6.  Validation performance of the ANN,  trained with exact measurements and tested with  noise-corrupted data( σ = 20 % )       x, true value0 0.2 0.4 0.6 0.8 100.20.40.60.81                                                           x, true value
Fig. 10.  Validation performance of the ANN,  trained with noise corrupted  measurements( σ = 10 % ), but tested with another  set of noise-corrupted data( σ = 5 % )
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