The correction ratio of environment effect to PE-4 and emulex explosive in tropical region and modeled using artificial intelligence

Scientists have investigated the blast wave profile produced by an explosive detonation for decades. The blast wave propagation profile has been estimated under given parameters based on a large amount of experimental data. However, the explosion perfonnance may be effected by environment or topical (topical region) effect and unable to plot actual results. The project tries to find the gap ratio between actual experiment been done and tabled by the manufacturer. The project also developed the weight correction ratio between PE-4 (experiment) and Emulex at the same performance. On top of that, a prediction model using a Multilayer Pereeptron (MLP) network are developed. A total of 500 grams of PE-4 and Emulex were used in this experiment, which hang-up at the height of 1.2 meters above the ground. The device was detonated at distances of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0. 3.5, and 4.0 meters. The best training technique for modelling Explosive Blast Prediction is the Bayesian Regularization (BR) training algorithm.