# Application of Bayesian Neural Network (BNN) for the Prediction of Blast-Induced Ground Vibration
## 1 Introduction  
Rock blasting is one of the most common and cost-effective techniques in mining and civil engineering operations [1]. blasting is a widely used mining technique for metal and non-metal resources, such as hard rock mining excavation and quarrying. In quarry operations, blasting requires drilling multiple rows of blast holes, with a specific spacing, burden, stemming, sub drill, face angle, bench height, and hole diameter. According to [PERSON] et al. [2], around 30% of the energy from the whole explosion is effectively utilized to break up the rock during rock blasting, whereas the remaining energy is wasted in different ways, such as in blasting vibration, fly rock, back break, air overpressure, etc. These activities have various environmental effects and create issues for those in close proximity to the blasting zone [3]; ground vibration is one of the most severe environmental effects of blasting. This can cause damage to structures and ultimately affect peoples' lives and possessions, particularly if the buildings and structures were not designed to resist the blast's enormous destruction. According to [PERSON] et al. 's [4] studies, blast-induced ground vibration affects vegetation growth and can lead to deforestation. Moreover, it causes ground and slope instabilities, affecting the safety of workers during loading, drilling, and subsequent blasting activities. Additionally, people who live or work near the explosion site may experience pain and discomfort because of ground vibrations [5; 6; 7]. The release of energy that occurs during the explosion is what causes ground vibration, and the intensity of the vibration is determined by several parameters, including the amount of explosive employed, the type of rock, which is blasted, and the distance fromthe source of the blast. According to [PERSON] et al. [7], the intensity of the blast-induced ground vibration is associated with the controllable and uncontrollable parameters of the blasting operations. The controllable blasting parameters, which include blast design parameters such as the burden, spacing, blast hole depth, diameter of the hole, stemming type and height, maximum charge weight used per delay (W), and specific charge, as well as explosive parameters such as the explosive type, detonation velocity (VoD), and powder factor, are all easy to modify, and planned based on the conditions; therefore, the blasting engineer is responsible for modifying and planning the controllable blasting parameters during the blasting design process. The uncontrolled parameters include the mechanical and physical properties of the rock, as well as the geological characteristics of the surrounding environment; the majority of uncontrolled aspects depend on the rock's natural formation. The ground vibration movement is like a wave pattern, that travels in a circumferential direction outward from the source of the blasting. This wave motion is analogous to the ripples that travel in a circumferential direction outward when an item is thrown into a body of water and causes an impact. The peak particle velocity (PPV) is the standard baseline parameter for calculating the amount of blast-induced ground vibration, according to the rules regulating the research into blasting practice and blast-induced ground vibration. This is because the PPV is a measurement of the velocity of the most forward particles in terms of transverse (T), vertical (V), and longitudinal (L) velocities. Various researchers have developed empirical equations to predict the intensity of blast-induced ground vibration, such as the equation that was the first meaningful PPV predictor, suggested by the United States Bureau of Mines (USBM), [PERSON], and [PERSON]. After a few years, different researchers modified the USSBM formula, based on the scaled distance and MIC. These techniques are mathematically expressed in Equations (1)-(4).