R Gholami - Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Iran,
A .Kamkar-Rouhani - Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Iran,
F. Doulati Ardejani - Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Iran,
Sh. Maleki - Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Iran,

Groundwater and soil pollution are noted to be the worst environmental problem related to the mining industrybecause of the pyrite oxidation, and hence acid mine drainage generation, release and transport of the toxic metals.The aim of this paper is to predict the concentration of Ni and Fe using a robust algorithm named support vectormachine (SVM). Comparison of the obtained results of SVM with those of the back-propagation neural network(BPNN) indicates that the SVM can be regarded as a proper algorithm for the prediction of toxic metalsconcentration due to its relative high correlation coefficient and the associated running time. As a matter of fact, theSVM method has provided a better prediction of the toxic metals Fe and Ni and resulted the running time fastercompared with that of the BPNN.

Prediction, Toxic metals, Support vector machine, Sarcheshmeh cooper mine, Back-Propagation neural network