Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction|
Shirani Faradonbeh, R; Jahed Armaghani, D; Abd Majid, M. Z.; Tahir, M. MD; Ramesh Murlidhar, B.; Monjezi, M. & Wong, H. M.
Blasting is a widely used technique for rock
fragmentation in opencast mines and tunneling projects.
Ground vibration is one of the most environmental effects
produced by blasting operation. Therefore, the proper prediction
of blast-induced ground vibrations is essential to
identify safety area of blasting. This paper presents a predictive
model based on gene expression programming (GEP)
for estimating ground vibration produced by blasting operations
conducted in a granite quarry, Malaysia. To achieve
this aim, a total number of 102 blasting operations were
investigated and relevant blasting parameters were measured.
Furthermore, the most influential parameters on
ground vibration, i.e., burden-to-spacing ratio, hole depth,
stemming, powder factor, maximum charge per delay, and
the distance from the blast face were considered and utilized
to construct theGEPmodel. In order to show the capability of
GEP model in estimating ground vibration, nonlinear multiple
regression (NLMR) technique was also performed
using the same datasets. The results demonstrated that the
proposed model is able to predict blast-induced ground
vibration more accurately than other developed technique.
Coefficient of determination values of 0.914 and 0.874 for
training and testing datasets of GEP model, respectively
show superiority of this model in predicting ground vibration,
while these values were obtained as 0.829 and 0.790 for
Blasting; Ground vibration; Gene expression programming; Nonlinear multiple regression