基于优化BP神经网络的气象环境下军事通信效能评估  

Evaluation of Military Communication Effectiveness in Meteorological Environment Based on Optimized BP Neural Network

作　　者：邱少明 王雪珂 杜秀丽[1] 吕亚娜 QIU Shao-ming;WANG Xue-ke;DU Xiu-li;LYU Ya-na(Key Laboratory of Communication and Network,Dalian University,Dalian 116622,China)

机构地区：[1]大连大学通信与网络重点实验室,辽宁大连116622

出　　处：《火力与指挥控制》2022年第3期89-96,共8页Fire Control & Command Control

基　　金：装备发展部预研基金资助项目(6140002010101,6140001030111)。

摘　　要：气象条件对作战的各个方面都产生不同程度的影响和制约,恶劣的天气情况会影响军事通信质量,为提高在气象环境影响下的军事通信效能评估效果,将BP(Back Propagation)神经网络模型应用于军事通信效能评估中,并结合基于信息素的细菌觅食改进算法(Bacterial Foraging Optimization based Pheromone,BFOP)进行求解,对BP神经网络参数进行优化。BFOP算法引入信息素思想,通过信息素浓度标识细菌经过的环境信息,指引细菌向信息素浓度高的位置进行迁移。仿真结果表明,所提评估模型具有更高的全局寻优能力,能更好地对军事通信效能进行评估,评估结果更准确。Meteorological conditions have different degrees of influence and restrictions on all aspects of combat.Severe weather conditions will affect the quality of military communications.In order to improve the evaluation effectiveness of military communications under the influence of meteorological environment,the BP(Back Propagation)neural network model is applied in the military communication effectiveness evaluation,combined with the Bacterial Foraging Optimization based Pheromone(BFOP)to make resolution and optimize the BP neural network parameters.The BFOP algorithm introduces the idea of pheromone,uses the pheromone concentration to identify the environmental information that the bacteria pass through,and guides the bacteria to migrate to a location with high pheromone concentration.The simulation results show that the proposed evaluation model has a higher global optimization capability,and can better evaluate military communication effectiveness,and the evaluation results are more accurate.

关 键 词：细菌觅食算法 迁移算子 信息素浓度 BP神经网络 效能评估 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置] TP212[自动化与计算机技术—控制科学与工程]