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Published in: Geotechnical and Geological Engineering 3/2015

01-06-2015 | Original paper

Classification of Stability of Highwall During Highwall Mining: A Statistical Adaptive Learning Approach

Authors: K. Ram Chandar, Chiranth Hegde, Mohan Yellishetty, B. Gowtham Kumar

Published in: Geotechnical and Geological Engineering | Issue 3/2015

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Abstract

The depleting coal deposits day by day required the introduction of novel methods of mining like highwall mining. Highwall mining is a method of extraction of coal blocked in the highwall. The method involves considerable challenges in the area of roof control and most importantly the stability of the highwall itself. Highwall mining has gained considerable importance all over the world, owing to the fact that the coal otherwise would not be extracted forever. This paper aims to assess the influence of varying conditions which can affect the stability of the highwall during highwall mining. The effect of gallery length, width of pillar and number of galleries are systematically studied through field investigations where a highwall mining was adopted first time in India. Initially, assessment was carried out using a numerical modelling approach and then the stability of the highwall is classified using multilinear regression, logistic regression and naive Bayes classifier. This will provide a mechanism to predict the stability of the highwall in future cases of similar conditions. The classification is done using statistical adaptive learning methods and a comparison of the methods is done.

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Metadata
Title
Classification of Stability of Highwall During Highwall Mining: A Statistical Adaptive Learning Approach
Authors
K. Ram Chandar
Chiranth Hegde
Mohan Yellishetty
B. Gowtham Kumar
Publication date
01-06-2015
Publisher
Springer International Publishing
Published in
Geotechnical and Geological Engineering / Issue 3/2015
Print ISSN: 0960-3182
Electronic ISSN: 1573-1529
DOI
https://doi.org/10.1007/s10706-014-9836-6

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