Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6661
Title: Estimation of Hardgrove grindability index of Turkish coals by neural networks
Authors: Özbayoğlu, Gülhan
Özbayoğlu, Ahmet Murat
Özbayoğlu, M. Evren
Keywords: Hardgrove grindability index
Turkish coals
neural networks
non-linear regression
proximate analysis
petrographic analysis
Issue Date: 2008
Publisher: Elsevier Science Bv
Abstract: 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. (C) 2007 Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.minpro.2007.08.003
https://hdl.handle.net/20.500.11851/6661
ISSN: 0301-7516
1879-3525
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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