Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS
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Abstract
The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66 MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R 2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R 2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS |
Series title | International Journal of Coal Preparation and Utilization |
DOI | 10.1080/19392699.2010.527876 |
Volume | 31 |
Issue | 1 |
Year Published | 2011 |
Language | English |
Publisher | Taylor & Francis Online |
Description | 11 p. |
First page | 9 |
Last page | 19 |
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