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Estimation of Hardgrove grindability index of Turkish coals by neural networks
Date
2008-01-31
Author
Ozbayoglu, Gulhan
ÖZBAYOĞLU, AHMET MURAT
Ozbayoglu, M. Evren
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In this research, different techniques for the estimation of coal HGI values are studied. Data from 163 sub-bituminous coals from Turkey are used by featuring I I coal parameters, which include proximate analysis, group maceral analysis and rank. Nonlinear regression and neural network techniques are used for predicting the HGI values for the specified coal parameters. Results indicate that a hybrid network which is a combination of 4 separate neural networks gave the most accurate HGI prediction and all of the neural network models, outperformed non-linear regression in the estimation process.
Subject Keywords
Geotechnical Engineering and Engineering Geology
,
Geochemistry and Petrology
URI
https://hdl.handle.net/11511/66627
Journal
INTERNATIONAL JOURNAL OF MINERAL PROCESSING
DOI
https://doi.org/10.1016/j.minpro.2007.08.003
Collections
Department of Mining Engineering, Article
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G. Ozbayoglu, A. M. ÖZBAYOĞLU, and M. E. Ozbayoglu, “Estimation of Hardgrove grindability index of Turkish coals by neural networks,”
INTERNATIONAL JOURNAL OF MINERAL PROCESSING
, pp. 93–100, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66627.