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In this paper, an electromagnetic stochastic finite element method is presented to calculate the statistical moments of electromagnetic problems with spatially uncertain dielectric parameters. First, the random field model of the dielectric material is represented by the Karhunen–Loeve expansion and inserted into the scalar Helmholtz wave equations. The stochastic equilibrium equations are thus constructed according to the node-based finite element method. Second, the first-order and second-order perturbation stochastic finite element methods are developed for calculating the statistical moments of electromagnetic responses. Finally, the feasibility and validity of the proposed method are verified by three numerical examples.

The sintering process possesses strong nonlinear, strong coupling, time-varying and time-delay characters. In this paper, an adaptive control method based on fuzzy neural network is proposed by integrating adaptive control, neural networks and fuzzy control, and has been used to control the burning through point in the sintering process. The fuzzy control rules are reflected in the neural network, and can be obtained by self-learning of neural network. An identification model is used to identify the dynamic characters of the sintering process on-line, and improves the ability of control precision and self- adaptability. The results of actual runs show the effectiveness of the proposed method.