| Title: | Characterization of Slovenian coal and estimation of coal heating value based on proximate analysis using regression and artificial neural networks |
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| Authors: | ID Kavšek, Darja (Author)
ID Bednárová, Adriána (Author)
ID Biro, Miša (Author)
ID Kranvogl, Roman (Author)
ID Brodnjak-Vončina, Darinka (Author)
ID Beinrohr, Ernest (Author) |
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| Files: |  Open_Chemistry_2013_Kavsek_et_al._Characterization_of_Slovenian_coal_and_estimation_of_coal_heating_value_based_on_proximate_analysis_us.pdf (749,77 KB)
MD5: CED22FDA5AB9046E84918F6390EE5B7A
 http://www.degruyter.com/view/j/chem.2013.11.issue-9/s11532-013-0280-x/s11532-013-0280-x.xml
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FKKT - Faculty of Chemistry and Chemical Engineering
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| Abstract: | Chemical composition of Slovenian coal has been characterised in terms of proximate and ultimate analyses and the relations among the chemical descriptors and the higher heating value (HHV) examined using correlation analysis and multivariate data analysis methods. The proximate analysis descriptors were used to predict HHV using multiple linear regression (MLR) and artificial neural network (ANN) methods. An attempt has been made to select the model with the optimal number of predictor variables. According to the adjusted multiple coefficient of determination in the MLR model, and alternatively, according to sensitivity analysis in ANN developing, two descriptors were evaluated by both methods as optimal predictors: fixed carbonand volatile matter. The performances of MLR and ANN when modelling HHV were comparable; the mean relative difference between the actual and calculated HHV values in the training data was 1.11% for MLR and 0.91% for ANN. The predictive ability of the models was evaluated by an external validation data set; the mean relative difference between the actual and predicted HHV values was 1.39% in MLR and 1.47% in ANN. Thus, the developed models could be appropriately used to calculate HHV. |
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| Keywords: | Slovenian coal, higher heating value, HHV, regression, artificial neural network |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Year of publishing: | 2013 |
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| Number of pages: | str. 1481-1491 |
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| Numbering: | Letn. 11, št. 9 |
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| PID: | 20.500.12556/DKUM-65391  |
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| ISSN: | 1895-1066 |
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| UDC: | 66:004.5 |
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| ISSN on article: | 1895-1066 |
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| COBISS.SI-ID: | 17017878 |
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| DOI: | 10.2478/s11532-013-0280-x |
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| NUK URN: | URN:SI:UM:DK:BOTBT0OQ |
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| Publication date in DKUM: | 03.04.2017 |
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| Views: | 29409 |
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| Downloads: | 440 |
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| Metadata: |    |
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| Categories: | Misc.
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