Abstract
Ground vibration is an integral part of the rock blasting process in surface mines, which may cause severe damages to structures and plants in the nearby environment. Therefore, its prediction plays an important role in the minimization of environmental impacts. The peak particle velocity (PPV) is an important predictor for ground vibration. In this paper, first a fuzzy logic model was developed to predict PPV based on collected data from blasting events in Sarcheshmeh copper mine, located in the southwest of Iran. The predictive fuzzy model was implemented on the fuzzy logic toolbox of MATLAB using the Mamdani algorithm. Then, the PPV was predicted by conventional empirical predictors used in blasting practice and also by multiple regression analysis. Finally, a comparative analysis between the results obtained by the fuzzy model and common vibration predictors was carried out. The results indicated the high predictive capacity of fuzzy model, which can be used as a reliable predictor of ground vibration for the studied mine.
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