2013
DOI: 10.1080/17415977.2013.854354
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Determination of space–time-dependent heat source in a parabolic inverse problem via the Ritz–Galerkin technique

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Cited by 25 publications
(17 citation statements)
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“…A survey in the literature shows that inverse problems have been studied so far in various issues such as source identification in the heat conduction [1][2][3][4][5] and wave propagation problems, [6][7][8][9] determination of material parameters [10][11][12][13][14] and inverse boundary conditions reconstruction. [15][16][17] The problem of inverse source identification on thin plates is also another interesting topic which has been investigated in numerous studies.…”
Section: Introductionmentioning
confidence: 99%
“…A survey in the literature shows that inverse problems have been studied so far in various issues such as source identification in the heat conduction [1][2][3][4][5] and wave propagation problems, [6][7][8][9] determination of material parameters [10][11][12][13][14] and inverse boundary conditions reconstruction. [15][16][17] The problem of inverse source identification on thin plates is also another interesting topic which has been investigated in numerous studies.…”
Section: Introductionmentioning
confidence: 99%
“…Due to the instability of the inverse problem, the computational treatment of such problems needs applying more accurate numerical methods to obtain a stable approximate solution. In recent years, IHCPs have been investigated from the analytical and numerical point of view, in the literature, e.g., [3][4][5][6][8][9][10].…”
Section: Introductionmentioning
confidence: 99%
“…In conclusion, the large sets of collocation points are not needed for applying the supplemented boundary conditions which naturally leads to a system of algebraic equations of smaller size and hence reduces the computation time. Although the authors in [20,21] reported satisfactory results with relatively low-cost computational efforts, their solution could suffer from propagation of errors because improperly posed problems are always involved with noisy input data. Since the satisfier function incorporates all initial and boundary conditions including the possibly erroneous ones, the technique has some shortcomings.…”
Section: Introductionmentioning
confidence: 99%