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Accurate price forecasts on the European Union Emissions Trading System (EU ETS) market are of interest to many production and investment entities. The article presents a new approach, which models the most significant determinants by the use of a rule-based model containing facts written in the form of ordered fuzzy numbers, as the description of trends of imprecise values of prices. This approach allows for a qualitative analysis of potential values and directions of EU allowance (EUA) price changes and their trends along with the probability of their occurrence in the future. Article presents a wide set of factors used for the analysis of EUA price conditions and the comparison of the results of various feature selection methods (Hellwig's method, F-test, Neighborhood Component Feature Selection method, RreliefF method). Another scientific value added to the presented research results is a new approach to modeling an influence of the significant determinants for a day-ahead pre ....

European Union Emissions Trading System , Neighborhood Component Feature Selection , Carbon Dioxide Emissions , Carbon Price , European Union Emissions Trading System , Feature Selection , Rdered Fuzzy Numbers ,