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Estimation of Hardgrove grindability index of Turkish coals by neural networks
Authors:Gülhan Özbayo?lu  A Murat Özbayo?lu  M Evren Özbayo?lu
Institution:1. Department of Mining Engineering, Middle East Technical University, Ankara 06531, Turkey;2. Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey;3. Department of Petroleum and Natural Gas Engineering, Middle East Technical University, Ankara 06531, Turkey
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 11 coal parameters, which include proximate analysis, group maceral analysis and rank. Non-linear 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.
Keywords:Hardgrove grindability index  Turkish coals  Neural networks  Non-linear regression  Proximate analysis  Petrographic analysis
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