A Matlab-Based Neural Network Model for Predicting Blast-Induced Ground Vibration

This research delves into using an artificial neural network (ANN) to forecast blast-induced ground vibration, vital for controlling the impact of blasting on nearby residential areas. By leveraging data from Singareni mines, the ANN model incorporates various input parameters to predict ground vibration intensity (peak particle velocity). With a dataset of 150 entries and sensitivity analysis, the ANN demonstrates a robust regression coefficient of 0.92, signifying its predictive strength. Comparative analysis favors the ANN model, showcasing its potential in mitigating adverse effects on residential zones, marking a significant stride in managing blast-induced ground vibration prediction using ANN.