We regard a magnetic inverse problem as a spatial optimum allocation problem of currents and use a Hopfield neural network for solving this optimization problem. Because the Hopfield neural network has an initial state problem that the optimum solution cannot be obtained unless an initial state of network is set up suitably, adoption of a genetic algorithm is proposed for solving this initial state problem of Hopfield neural network. The effectiveness of proposed method is confirmed by computational simulations.

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This paper proposes the inverse estimation method of current distribution from magnetic fields by a combination method of genetic algorithm (GA) and neural-network. We regarded the estimation problem of current distribution as an optimum allocation problem of currents and used GA and neural-network to solve this optimum problem. Case stdies with computer simulation showed its effectiveness.

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