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Anais do 9. Congresso Brasileiro de Redes Neurais
In this article, we present a method to approximate the decision-maker utility function in a decision model based on the multiattribute utility theory (MAUT). This approximation is built using through the construction of a partial sorting for the feasible alternatives named ranking and an artificial neural network, which captures informations of the original utility function through this ranking. We present one utility function model and the results obtained using the proposed method.doi:10.21528/cbrn2009-045 fatcat:pc3oxlgbdra6xa5sceg3lfyp5y