Prediction of Acid Mine Drainage Generation Potential of A Copper Mine Tailings Using Gene Expression Programming-A Case Study
- سال انتشار: 1399
- محل انتشار: مجله معدن و محیط زیست، دوره: 11، شماره: 4
- کد COI اختصاصی: JR_JMAE-11-4_014
- زبان مقاله: انگلیسی
- تعداد مشاهده: 331
نویسندگان
Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran
Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran
Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran
School of Mining, College of Engineering, University of Tehran, Tehran, Iran
چکیده
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 ۳۰% of the data is chosen as the training data randomly, while the validation data is included in ۷۰% of the dataset. Subsequently, the relationships are proposed using GEP. The high values of correlation coefficients (۰.۹۲, ۰.۹۱, ۰.۸۶, and ۰.۸۹) as well as the low values of RMS errors (۰.۱۴۰, ۰.۰۱۴, ۱۵۰.۳۰۱, and ۰.۵۴۳) 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.کلیدواژه ها
Acid Mine Drainage, copper tailing, pyrite, Chalcopyrite, Gene expression programmingاطلاعات بیشتر در مورد COI
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