Optimization of electromagnetic devices using artificial neural network with quasi-Newton algorithm

The paper proposes a method for the design optimization of electromagnetic devices. It utilizes an artificial neural network with the quasi-Newton algorithm. The proposed method can determine optimal weights and biases in the neural network more rapidly than the conventional method. A simple electromagnetic device is optimized by using this method. The paper reviews several optimization techniques for learning in multilayer neural networks. From the results of comparative numerical simulations, it proposes a method to construct the nonlinear mapping function more rapidly than the conventional algorithm, that is, the error back-propagation proposed by Rumelhart et al. (1986)