Research On Firepower Planning And Simulation Verification For Combat Effectiveness

Firepower planning is a forward-looking total factor strategic planning carried out before combat.The purpose is to maximize the impact on the enemy with the minimum damage and resource consumption under the premise of completing the mission.In modern war,more and more kinds of combat elements and more and more complex combat schemes lead to the rapid expansion of the space dimension of firepower planning schemes.Traditional firepower planning is difficult to solve the problem of high-dimensional complex planning,so it is urgent to build a more scientific and comprehensive evaluation planning model that integrates multiple operational elements and to find a suitable solution method according to the high-dimensional complexity of the model.This paper focuses on the firepower planning for combat effectiveness,constructs the firepower planning model with combat effectiveness as the target,studies the solution of the high-dimensional discrete model,and gives the suitable algorithm for the multidimensional model,in order to provide the basis for the pre-war platoon arrangement.The main research contents of this paper are as follows:(1)In view of the shortcomings of the existing firepower planning model,the combat effectiveness of the comprehensive evaluation scheme is proposed as the objective function of the firepower planning model,and the integrated damage tree,Monte Carlo,and other methods are used to build the overall framework of the firepower planning model.(2)Analyze the main factors affecting combat effectiveness,model the evaluation criteria of combat effectiveness based on the value,hit,damage,consumption,and other indicators,and build a mathematical model of firepower planning based on the feasible solution space of combat effectiveness and firepower planning.(3)According to the characteristics of the fire planning model,the ant colony algorithm of the swarm intelligence algorithm is used to solve the model.Aiming at the problem of the generation of ant colony algorithm pheromone generation rule applied to the model in this paper is improved.(4)In view of the limitations of the swarm intelligence algorithm in solving highdimensional discrete space,the reinforcement learning algorithm based on the Q algorithm is applied to solve and analyze the model in this paper.In view of the defects of the Q algorithm and non-uniform overestimation in fire planning research,the DQN algorithm and Double DQN algorithm are introduced to solve and analyze the model.(5)Based on the modeling and evaluation analysis method in this paper,the firepower planning and effectiveness evaluation modeling are carried out around a certain combat scenario,and the ant colony algorithm and reinforcement learning algorithm are combined to solve the model and verify the simulation.The simulation results show that the firepower planning model and solution method established in this paper provide a feasible firepower planning solution for the increasingly complex modern battlefield,which has a good reference significance.