Abstract
An intelligent system for the design optimization of electromagnetic devices is presented. The system comprises a back-propagation neural network in conjunction with an optimizing Hopfield Net for performing search and optimization functions. An adaptive algorithm is used to improve the response of the system in a dynamic environment. Data can be input by an experienced designer in addition to a case generator from the finite element (FE) solutions. Optimal designs are obtained quickly once the artificial neural network (ANN) is trained with a variety of topologies. Results of implemented examples are provided to show the effectiveness of the proposed system. >
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