Design optimization of geometric boundaries in electromagnetic devices by artificial neural networks

A method for the optimal design of electromagnetic devices is presented. The method uses artificial neural networks (ANNs) in a design environment which encompasses numerical computations and an expert's input for generating a variety of ANN training data. Results of two implementation examples are provided. The optimal design is obtained quickly (in a matter of milliseconds) once the ANNs are trained with a variety of geometrical topologies. The procedure explained here can be used to provide good initial designs for use with iterative search techniques to reduce searching time. This aspect is highly desirable for increasing the effectiveness of the optimal design procedure.<
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