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Cgm-spso algorithm for 2D steady state boundary shape inversion based on temperature information

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Document pages: 12 pages

Abstract: For the identification of two-dimensional steady-state thermal boundary, a hybrid algorithm of conjugate gradient method and social particle swarm optimization (cgm-spso) algorithm is proposed. The global search ability of particle swarm optimization algorithm and the local search ability of gradient algorithm are effectively combined, which overcomes the disadvantage that conjugate gradient method is easy to converge to local solution and heavily depends on the initial approximation of iterative process. The hybrid algorithm also avoids the problem that particle swarm optimization algorithm needs a lot of iterative steps and a lot of time. Experimental results show that the algorithm is feasible and effective in solving two-dimensional problemsional steady-state thermal boundary shape.

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