Hybrid multilayer perceptron network for explosion blast prediction

For decades, scientists have studied the blast wave profile produced by an explosive detonation. Based on a significant amount of experimental data, the blast wave propagation profile has been predicted under given parameters. However, most studies have only looked at the central point of initiation for spherical fonn explosives. The purpose of this research is to compare the blast pressure readings of shaped charges on the blast profiles of Emulcx and PE-4, as well as to develop a prediction model using a Hybrid Multilayer Pereeptron (HMLP ) network. This experiment, which began at a distance of 1.2 meters from the ground, employed a total of 500 grams of military explosive and Emulex. At distances of 0.5, 1.0, 1.5,2.0,2.5,3.0, .3.5, and 4.0 meters, the bomb was exploded. The Bayesian Regularization (BR) training algorithm is the best training strategy for modelling Explosive Blast Prediction.