Backbreak is an undesirable phenomenon in blasting operations, which can bedefined as the undesirable destruction of rock behind the last row of explosive holes. To prevent and reduce its adverse effects, it is necessary to accurately predict backbreak in the blasting process. For this purpose, the data obtained from 66 blasting operations in Gol-e-Gohar iron ore mine No. 1 considering blast pattern design Parameters and geologic were collected. The Pearson correlation results showed that the parameters of the hole height, burden, spacing, specific powder, number of holes, and the uniaxial compressive strength had a significant effect on the backbreak. In this study, a multilayer perceptron artificial neural network with the 6-12-1 architecture and six multiple linear and nonlinear statistical models were used to predict the backbreakin the blasting operations. The results of this study demonstrated that the prediction rate of backbreak using the artificial neural network model with R2 = 0.798 and the rates of MAD, MSE, RMSE and, MAPE were0.79, 0.93, 0.97 and, 11.63, respectively, showed fewer minor error compared to statistical models. Based on the sensitivity analysis results, the most important parameters affecting the backbreak, including the hole height, distance between the holes in the same row, the row spacing of the holes, had the most significant effect on the backbreak, and the uniaxial compressive strength showed the lowest impact on it.

Mining activities from exploration to final material handling up to shipment pass through various stages where environmental pollution results. Mining method can and should be selected in such a way that their impact on individuals and environmental to be minimized. Until now, different mining specialists have carried out many studies on mining method selection. Unfortunately neither of previous approaches takes into account of the environmental consideration and methodology for assessment of environmental impacts criterion. This paper discusses environmental impacts of mining operations associated with different mining methods. For this purpose, the Folchi approach was modified for environmental impact assessment which associates the mining methods inherently and developed of a procedure to assist a selecting of mining method. Firstly, the general and explanatory information about effects of mining on the environmental pollution are given in the paper. Moreover field and purposes of the study are introduced. The paper presents an environmental assessment for different mining methods. And, secondly, the impacts of each mining methods on environment are focused and discussed. Finally, some concluding remarks are made and the related applications for the mining method selection are discussed by using in a case study. As the main advantage, this new algorithm takes several environmental issues and their interaction takes into consideration for environmental assessment of a mining method selection.