Abstract
In this paper, a mathematical model of a neural network defuzzificator is presented. It is a two-layer perceptron and serves to convert a fuzzy solution to a numerical form in fuzzy-logic output procedures. The model allows optimizing the computational load that occurs when using the standard center-of-gravity method, through the use of a neural network. Training and testing are conducted with various settings of the neural-network model. The effectiveness of this approach by measuring the time required for the computation is also proved.
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