AUTOMATIC RANKING OF FUZZY NUMBERS WITH THE CRITERION OF A DECISION-MAKER LEARNT BY AN ARTIFICIAL NEURAL-NETWORK

In a previous work, we indicated that Artificial Neural Networks (ANN) would be able to learn to compare fuzzy numbers as a real decision ma ker does. In this paper, we describe in detail the experiment that we have developed to that goal, and in which we have obtained good result s. We apply this trained ANN to some decision problems with fuzzy envi ronment, by means of the automatic ranking of the decision problem uti lities, performed as trapezoidal fuzzy numbers. So, we use the trained ANN as a personal method to compare fuzzy numbers. We have trained a multilayer feedforward ANN with the criterions (to compare fuzzy numbe rs) of three people, each with different characteristic, using the bac kpropagation algorithm and different structures. Then we use this trai ned ANN to rank a set of fuzzy numbers which can be considered as util ities of decision problems with fuzzy environment, hence enabling us t o make the best choice. Several examples are shown also.