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To deal with the ill-posed nature of the inverse heat conduction problem(IHCP), the regularization parameter alpha can be incorporated into aminimization problem, which is known as Tikhonov regularization method, apopular technique to obtain stable sequential solutions. Because alpha is apenalty term, its excessive use may cause large bias errors. Ridge regressionwas developed as an estimator of the optimal alpha to minimize the magnitude ofa gain coefficient matrix appropriately. However, the sensitivity coefficientmatrix included in the gain coefficient matrix depends on the time integrator;thus, certain parameters of the time integrators should be carefully consideredwith alpha to handle instability. Based on this motivation, we propose aneffective iterative hybrid parameter selection algorithm to obtain stableinverse solutions.

Optimal hybrid parameter selection for stable sequential solution of inverse heat conduction problem