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Title: Hardgrove Grindability Index Estimation Using Neural Networks
Authors: Özbayoğlu, Gülhan
Özbayoğlu, Ahmet Murat
Issue Date: 2008
Source: Özbayoglu, A.M. and G. Özbayoglu. Hardgrove Grindability Index Estimation using Neural Networks”, International Mineral Processing Symposium (IMPS 2008), Antalya, Turkey.
Abstract: In a previous study, different techniques for the estimation of coal HGI values were investigated (Özbayoğlu, 2008). As continuation of that research, in this study a revised neural network methodology is used for estimating the HGI values using the same data from 163 sub-bituminous coals from Turkey. The parameter set used for estimating HGI consisted of moisture, ash, volatile matter and Rmax ratios. These 4 coal parameters were fed into different neural network topologies. The network parameters were optimized by genetic algorithms. The test results indicate that estimation rate was improved %10-15 over the previous results (Özbayoğlu, 2008) by using this new parameter set and optimized neural network configurations.
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering

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