Decor A hybrid algorithm and regularization method are proposed, for the first time, to solve the one-dimensional degenerate inverse heat conduction problem to estimate the initial temperature distribution from point measurements.The evolution of the heat is given by a degenerate parabolic equation with singular potential.This problem can be formulated in a least-squares framework, an iterative procedure which minimizes the difference between the given measurements and the value at sensor locations of a reconstructed field.The mathematical model leads to a nonconvex minimization problem.
To solve it, we prove the existence of at least one solution of problem and we propose two approaches: the first is based on a Tikhonov regularization, while the second approach is Dishwasher Front Escutcheon Panel based on a hybrid genetic algorithm (married genetic with descent method type gradient).Some numerical experiments are given.