… is shown by determining the peak particle velocity (PPV) [11,12,… study, Verma and Singh [4]
employed NN, support vector … 3 shows the recorded particles velocity related to one blasting …

… Peak particle velocity (PPV) and frequency are the most … those of an ANN and a support
vector machine (SVM). BGAMs … response surface model (RSM) and support vector regression (…

… the peak particle velocity (PPV) remains largely unexplored. … Support vector machine (SVM)
is one of the most frequently … of this study) to predict PPV induced by blasting using MC and …

… a support vector regression model optimised by particle swarm … In this study, the blasting
datasets upon which the models were … The peak particle velocity (PPV) values were used as the …

… to predict BIRM during bench blasting, and the analysis … feasibility of using the optimized
support vector machine (SVM… the novel BIRM prediction model and two case studies were …

… to fragment the rock masses in the surface mines as well as tunneling … Support vector
machine (SVM) and empirical models were used for predicting the blast-induced AOp in the study …

… these proposed models, a case study was carried out in Johor, … and peak particle velocity
(PPV) caused by blasting were … ,” and “support vector machine” are also represented in this …

… network model for the prediction of blasting operations in five … blasting point (D) and a charge
per delay (Q) were the two input parameters into the model while the peak particle velocity (…

… where \(f(x_{i} )\) is the predicted results, \(\alpha_{i}^{*}\) and \(\alpha\) represent Lagrange
… b is a parameter in the regression using support vector machine. The decision tree (Kamiński …

… this study was to, firstly, use machine learning algorithms to predict Peak Particle Velocity
(PPV) in order to optimise blasting layouts and reduce the risk of damaging surface structures. …