Modelling of the AC-EAF process using computational intelligence methods

Time reduction of steel scraps meltdown is a really challenging problem. Typically this process is stochastic without any determinism and only simple and naive rules, based on linear electric circuits, are currently used to manage such processes. The goal of the paper is to present the way of building an accurate model concerning feature extraction methods and the use of artificial neural networks that would be helpful in predicting the maximum energy needed by the electric arc furnace.