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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/375

Title: Classification of coal seams with respect to their spontaneous heating susceptibility—a neural network approach
Authors: Panigrahi, D C
Sahu, H B
Keywords: adaptive resonance theory
classification of coal seams
spontaneous heating
Issue Date: 2004
Publisher: Kluwer
Citation: Geotechnical and Geological Engineering, Vol 22, No 4, P 457-476
Abstract: The paper presents the application of adaptive resonance theory of artificial neural networks (ANN) for classification of coal seams with respect to their proneness to spontaneous heating. In order to apply this technique, 31 coal samples have been collected from different Indian coalfields covering both fiery and non-fiery coal seams of varying ranks spreading over 8 different mining companies. The intrinsic properties of these samples have been determined by carrying out proximate, ultimate and petrographic analyses. The susceptibility indices of these samples have been studied by five different methods, viz. crossing point temperature, differential thermal analysis, critical air blast analysis, wet oxidation potential difference analysis and differential scanning calorimetric studies. Exhaustive correlation studies between susceptibility indices and the intrinsic properties have been carried out for identifying the appropriate spontaneous heating susceptibility indices and intrinsic...
Description: Copyright for this article belongs to Kluwer DOI: 10.1023/B:GEGE.0000047040.70764.90
URI: http://hdl.handle.net/2080/375
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