The fire control system is one of core parts of the tank,which plays an important role in im-proving tank firepower and survivability on the battlefield,so health prediction for the fire control sys-tem is particularly important.In order to improve the prediction accuracy,a health prediction method of fire control systems based on the improved particle swarm optimization algorithm and random forest algorithm(IPSO-RF algorithm)was proposed.First,the adaptive weight was introduced to improve the particle swarm optimization algorithm.Then the core parameters of the random forest algorithm were optimized and the health prediction model was established.Finally,the power module of the fire con-trol computer and sensor subsystem was selected as the experimental object and compared with LSTM,GSM-SVM,BAYES-RF and GSM-RF models.The experimental results show that the proposed method is superior to other models in terms of prediction accuracy and effect.
关键词
健康预测/随机森林/粒子群优化/火控系统
Key words
health prediction/random forest/particle swarm optimization/fire control system
维普
万方数据