Evaluation of blast-induced ground vibrations in open-pit mines by using adaptive neuro-fuzzy inference systems

This study addresses the effects of rock characteristics and blasting design parameters on blast-induced vibrations in the Kangal open-pit coal mine, the Tulu openpit boron mine, the Kirka open-pit boron mine, and the TKI C, an coal mine fields. Distance (m, R) and maximum charge per delay (kg, W), stemming (m, SB), burden (m, B), and S-wave velocities (m/s, Vs) obtained from in situ field measurements have been chosen as input parameters for the adaptive neuro-fuzzy inference system (ANFIS)based model in order to predict the peak particle velocity values. In the ANFIS model, 521 blasting data sets obtained from four fields have been used (r (2) = 0.57-0.81). The coefficient of ANFIS model is higher than those of the empirical equation (r (2) = 1). These results show that the ANFIS model to predict PPV values has a considerable advantage when compared with the other prediction models.TUBITAK (The Science and Technological Research Council of Turkey) [110M294]This study is supported by TUBITAK (The Science and Technological Research Council of Turkey) Project No. 110M294. The authors would also like to thank the staff of the Electricity Generation Company, Demir Export, Eti Mine, and TKI for their assistance during the field work