Prediction of Acid Mine Drainage Generation Potential of A Copper Mine Tailings Using Gene Expression Programming-A Case Study

Jodeiri Shokri, B.; Dehghani, H.; Shamsi, R.; Doulati Ardejani, F.

doi:10.22044/jme.2020.10031.1938

Document Type : Original Research Paper

Authors

¹ Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran

² School of Mining, College of Engineering, University of Tehran, Tehran, Iran

https://doi.org/10.22044/jme.2020.10031.1938

Abstract

This work presents a quantitative predicting likely acid mine drainage (AMD) generation process throughout tailing particles resulting from the Sarcheshmeh copper mine in the south of Iran. Indeed, four predictive relationships for the remaining pyrite fraction, remaining chalcopyrite fraction, sulfate concentration, and pH have been suggested by applying the gene expression programming (GEP) algorithms. For this, after gathering an appropriate database, some of the most significant parameters such as the tailing particle depths, initial remaining pyrite and chalcopyrite fractions, and concentrations of bicarbonate, nitrite, nitrate, and chloride are considered as the input data. Then 30% of the data is chosen as the training data randomly, while the validation data is included in 70% of the dataset. Subsequently, the relationships are proposed using GEP. The high values of correlation coefficients (0.92, 0.91, 0.86, and 0.89) as well as the low values of RMS errors (0.140, 0.014, 150.301, and 0.543) for the remaining pyrite fraction, remaining chalcopyrite fraction, sulfate concentration, and pH prove that these relationships can be successfully validated. The results obtained also reveal that GEP can be applied as a new-fangled method in order to predict the AMD generation process.

Keywords

References

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Prediction of Acid Mine Drainage Generation Potential of A Copper Mine Tailings Using Gene Expression Programming-A Case Study

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Volume 11, Issue 4October 2020Pages 1127-1140

Volume 11, Issue 4
October 2020
Pages 1127-1140