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 |
|---|---|
| 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 |
| Google Analytic Metrics | Metrics page |