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Advances in Continuous and Discrete Models

Theory and Modern Applications

Table 2 Error estimates between the exact and regularized solutions for \(\tau = 1.7\), \(\alpha \in \{0.65, 0.75, 0.85, 0.95\}\)

From: Identification of source term for the ill-posed Rayleigh–Stokes problem by Tikhonov regularization method

  ϵ
  0.1 0.01 0.001
  α = 0.65
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\) 0.111131774567399 0.047840847429863 0.040796403046666
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\) 0.104219494973211 0.047373969253811 0.040704667266564
  α = 0.75
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\) 0.042292184968334 0.032976631468816 0.025075858532616
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\) 0.118817648652812 0.028123860184860 0.024430674882777
  α = 0.85
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\) 0.130527372052525 0.022400766773086 0.014919116713563
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\) 0.082465125249822 0.020184320450563 0.014652593632991
  α = 0.95
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\) 0.045333767253358 0.011699213808191 0.008763429831879
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\) 0.044277712631869 0.008651113194266 0.008905712655202
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