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作 者:王亮[1] 童忠诚 WANG Liang;TONG Zhong-cheng(Institute of Electronic Countermeasure,National University of Defense Technology,Hefei 230037,China)
机构地区:[1]国防科技大学,安徽合肥230037
出 处:《舰船电子对抗》2022年第6期45-49,79,共6页Shipboard Electronic Countermeasure
摘 要:对作战系统效能进行评估时,通常运用层次分析法(AHP)来解决定性因素和定量因素相结合评价的问题。但是人为主观因素对该方法的评价结果影响较大,为此将逆传播(BP)神经网络与层次分析法相结合,构建AHP-BPNN模型来改进AHP法。以末端光电防护系统作战效能评估为例进行仿真研究,结果表明该模型可以有效降低系统评价过程中的主观影响,提高作战效能评估的准确性。When evaluating the effectiveness of a operation system,analytic hierarchy process(AHP)method is usually used to solve the problem of combining qualitative and quantitative factors.However,human subjective factors have a great impact on the evaluation results of this method.Therefore,back propagation neural network(BPNN)and analytic hierarchy process are combined to construct AHP-BPNN model to improve AHP.Simulation research is performed.Taking the operation effectiveness evaluation of terminal photoelectric defended system as an example,and the simulation results show that the model can effectively reduce the subjective influence in the system evaluation process and improve the accuracy of operation effectiveness evaluation.
关 键 词:电子对抗系统 末端光电防护 作战效能评估 AHP-BPNN
分 类 号:N945[自然科学总论—系统科学] TN977[电子电信—信号与信息处理]
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