Advances in Continuous and Discrete Models

Theory and Modern Applications

Table 1 Error estimates between the exact and regularized solutions for \(\tau = 1.6\), \(\alpha \in \{0.65, 0.75, 0.85, 0.95\}\)

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
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\)	0.067015108159255	0.047468902109316	0.041441591914833
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\)	0.098997404519191	0.044495631182970	0.040535488144887
	α = 0.75
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\)	0.084761583230752	0.028602688042509	0.024458932308338
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\)	0.053156432449751	0.028231628315379	0.024378712621981
	α = 0.85
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\)	0.130209694916768	0.021179319121018	0.015465349519243
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\)	0.122475577340357	0.024601414585993	0.015239026338959
	α = 0.95
\(\mathit{Err}^{\beta _{\mathrm{pri}}}\)	0.037276991722023	0.010256764619097	0.008742004875893
\(\mathit{Err}^{\beta _{\mathrm{pos}}}\)	0.134846446943958	0.010076794618172	0.009621545639896

Back to article page