Abstract:

Presentation of the train speed as a fuzzy number is justified by the impossibility to accurately predict this value. This is caused by deviation of many train and locomotive parameters in operating conditions. According to statistics, the actual train speed is different from the design speed by up to 5 km/h. According to the distribution of the speed deviation from the design value, a hypothesis about using t- and π-class membership functions was proposed. It was found that with the fuzziness coefficient values less than 2, it is necessary to use the triangular activation function to present the fuzzy variables. If the fuzziness coefficients are greater than 2, it is reasonable to use both classes of membership functions. This will allow to apply artificial intelligence theory methods in modeling the decision support system for locomotive crews. Author Biographies Тетяна Василівна Бутько, Ukrainian State Academy of Railway Transport Square Feuerbach, 7, Kharkov, Ukraine, 61050 Professor Management of operational work

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