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Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering. Surface Science Western, Research Park, University of Western Ontario, Canada.ORCID iD: 0000-0002-2265-6321
Surface Science Western, Research Park, University of Western Ontario, Candada.
West Virginia Geological and Economic Survey, USA.
Center for Applied Energy Research, University ofKentucky, USA.
2011 (English)In: International Journal of Coal Preparation and Utilization, ISSN 1939-2699, Vol. 31, no 1, p. 9-19Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Taylor & Francis, 2011. Vol. 31, no 1, p. 9-19
Keywords [en]
ANFIS, Gross calorific value, Mineral matter, Petrography, Regression
National Category
Mineral and Mine Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-72291DOI: 10.1080/19392699.2010.527876ISI: 000287085600002Scopus ID: 2-s2.0-79251491044OAI: oai:DiVA.org:ltu-72291DiVA, id: diva2:1272062
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2019-02-25

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Chelgani, Saeed Chehreh

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CiteExportLink to record
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  • apa
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Output format
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