Abstract:

In response to the fast calculation requirements for penetration datas under mobile launch conditions, an algorithm is proposed based on the combination of improved particle swarm optimization and back propagation (BP) neural network. The improved particle swarm algorithm optimizes the electronic interference penetration strategy at multiple fixed launch points in the combat area, and then trains the neural network for fitting, enabling the penetration strategy to achieve the goal of fast calculation. Considering the randomness of particle swarm optimization algorithm, by introducing quasi optimal solution particles during the initialization process and adding relevant constraints, the launch points in the launch area can quickly obtain the optimal solution and maintain good coherence and stability between adjacent points, providing a good training set for neural network training, and ultimately achieving the goal of rapid penetration planning at any point in the launch area. The relevant research methods have certain reference significance for the formulation and application of combat plans.

Key words: mobile launch, improved particle swarm optimization, neural network, electronic interference, datas computing