Design and implementation of bullet classification algorithm based on MCPSO

Shenyang military area "ultrasonic projectile interior component detection system" as the subject background, low energy ultrasound is used to detect the bullet. Based on neural network to capture data, so as to determine the specific types of waste, a kind of chaotic mutation particle swarm optimization algorithm (MCPSO) is put forward. The parameters of the neural network optimization and weight optimization are made into a unified framework, making full use of particle swarm algorithm optimization ability and fast convergence rate of characteristics. Relative to the general neural network structure optimization algorithm, parameters are less and computation complexity is easier. Finally the algorithm is applied to the bullet classification problems and gets good effect.