Predicting The Peak Particle Velocity at Tunnel Linings under The Impact of Blasting in Neighboring Tunnels

This paper examines the application of artificial intelligence models, specifically artificial neural networks (ANNs), to predict the peak particle velocity (PPV) at a tunnel lining resulting from nearby blasting. The ANN models are developed using data collected during the construction of the Hai Van 2 traffic tunnel, which connects Hue City and Da Nang City in Vietnam. The training and testing results above the training database and testing database (with a coefficient of determination R 2 of 0.9 913 and a mean square error MSE of 3.10 - 4 for the testing dataset, and R 2 = 0.9903 and MSE = 3.10 - 4 for the training dataset) demonstrate the model's high accuracy in predicting the peak particle velocity at the Hai Van 1 tunnel lining, relate to the impact of mine blasts during the construction of the Hai Van 2 tunnel.