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 |
本文献已被 ScienceDirect 等数据库收录! |
|