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- W2014873574 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." @default.
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- W2014873574 title "Estimation of Hardgrove grindability index of Turkish coals by neural networks" @default.
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- W2014873574 doi "https://doi.org/10.1016/j.minpro.2007.08.003" @default.
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