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Applied Water Science

, Volume 1, Issue 3–4, pp 125–134

First Online: 01 November 2011Received: 17 May 2011Accepted: 21 September 2011

Abstract

Groundwater and soil pollution are noted to be the worst environmental problem related to the mining industry because 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 vector machine 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 metals concentration due to its relative high correlation coefficient and the associated running time. As a matter of fact, the SVM method has provided a better prediction of the toxic metals Fe and Ni and resulted the running time faster compared with that of the BPNN.

KeywordsPrediction Toxic metals Support vector machine Sarcheshmeh cooper mine Back-propagation neural network  Download fulltext PDF



Author: R. Gholami - A. Kamkar-Rouhani - F. Doulati Ardejani - Sh. Maleki

Source: https://link.springer.com/







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