Abstract
This paper describes a neural network approach for modeling decision makers' fuzzy preference structures. A general feedforward neural network is introduced as a representation of membership function for fuzzy preference relations. A new learning algorithm is proposed for training the neural network to learn fuzzy preference structures. Simulation results show that the proposed neural network approach is capable of modeling a variety of fuzzy preference structures.
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