Inverse Problems Of Partial Differential Equations Particle Swarm Algorithm

Particle swarm optimization is a relatively new method of global optimization. In common with genetic algorithms, ant colony algorithm and other majority of evolutionary computation methods, PSO algorithm is also a class of stochastic optimization base on swarm intelligence algorithm, but in comparison with other evolutionary computation methods, PSO algorithm has advantage in converging fast, seting up less parameters, programming simple and having deep intelligence background. Therefore, PSO algorithm has been made immediately aroused optimization and scholars in related fields and optimization of widespread concern. The use of particle swarm algorithm for solving inverse problems of partial differential equations is the research focus of this article.This paper analyzes the study of particle swarm optimization algorithm in optimization applications, in particular the application of function optimization. This paper discussed improved algorithm deeply. Secondly, this paper explained the inverse problem of partial differential equations, analysis of the inverse problem ill-posedness. Finally, the problem of partial differential equations are solved by the finite element method. The finite element method and particle swarm optimization algorithm combined to complete two-dimensional parabolic equation of the inverse problem of the numenrical simulation.This paper prepared the corresponding numerical calculation procedure. The better results have been received in a number of numerical simulations of the inverse problem of model test. This paper reflected the effectiveness of the algorithm, versatility and robustness.