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Abstract
Lignite quality parameters have had central importance for power plants. This article addresses a comparative study on fuzzy and regression modeling for estimating the calorific value of lignite, which is one of the quality parameters from the other parameters: moisture, ash, volatile matter, and sulphur content. For the estimations, data driven models were designed based on linguistic fuzzy modeling structures. In addition, estimations of the fuzzy models were compared with linear regression estimations. The great majority of performance evaluations showed that the fuzzy estimations are very satisfactory in estimating calorific value of lignite.