Predicting the pyrite oxidation process within coal waste piles using multiple linear regression (MLR) and teaching-learning-based optimization (TLBO) algorithm

Entezam, Shima and Shokri, Behshad Jodeiri and Ardejani, Shaghayesh Doulati and Mirzaghorbanali, Ali ORCID: https://orcid.org/0000-0002-7967-9233 and McDougall, Kevin ORCID: https://orcid.org/0000-0001-6088-1004 and Aziz, Naj (2022) Predicting the pyrite oxidation process within coal waste piles using multiple linear regression (MLR) and teaching-learning-based optimization (TLBO) algorithm. In: 2022 Resource Operators' Conference, Feb 2022, University of Wollongong / University of Southern Queensland, Australia.


Abstract

Coal mining often leads to significant environmental hazards and health concerns when sulfide minerals, particularly pyrite, are associated with coal waste. The oxidation of pyrite typically generates acid mine drainage, a significant problem. This paper presents two mathematical relationships using a teaching-learning-based optimization (TLBO) algorithm for predicting pyrite oxidation and pH changes within a coal waste pile from Alborz-Markazi in northern Iran. A dataset was built based on historical data to achieve this goal. Some influential parameters comprising the depths of the various samples, oxygen fraction, and bicarbonate concentrations were considered as input data, while the outputs were pyrite content and pH. Then, the best statistical relationships were suggested between input and output parameters employing curve and surface fitting methods. Afterward, two multiple linear regression (MLR) models were presented for predicting pyrite content and pH. Also, two relationships have been suggested for predicting the same outputs by applying the TLBO algorithm. Comparison of the results of the latter method with the results obtained using the statistical technique, including correlation coefficient and root mean squared error (RMSE), revealed that the TLBO could predict the outcomes better than the MLR.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Engineering (1 Jan 2022 -)
Faculty/School / Institute/Centre: Current - Institute for Advanced Engineering and Space Sciences - Centre for Future Materials (1 Jan 2017 -)
Date Deposited: 19 Apr 2022 01:49
Last Modified: 09 May 2022 04:42
Uncontrolled Keywords: pyrite oxidation process; coal waste piles
Fields of Research (2020): 40 ENGINEERING > 4005 Civil engineering > 400502 Civil geotechnical engineering
40 ENGINEERING > 4019 Resources engineering and extractive metallurgy > 401902 Geomechanics and resources geotechnical engineering
40 ENGINEERING > 4019 Resources engineering and extractive metallurgy > 401905 Mining engineering
URI: http://eprints.usq.edu.au/id/eprint/47569

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