CAJ | 학술논문

针对目前多计算机生成兵力（ Computer Generated Force ，CGF）协同反潜中无法充分利用战场信息实现CGF搜潜策略优化的问题，在CGF间可有效实现信息交互的前提下，将信息融合技术引入到反潜作战仿真中；利用BP （Back Propagation）人工神经网络获取证据信息的基本置信分配，通过改进的D-S（Dempster-Shafer）证据理论对反潜CGF获取的信息进行综合，以此改进反潜CGF的移动策略。仿真实验表明，在反潜CGF搜潜过程中引入人工神经网络和信息融合技术，可有效提高CGF搜潜的成功率。
침대목전다계산궤생성병력（ Computer Generated Force ，CGF）협동반잠중무법충분이용전장신식실현CGF수잠책략우화적문제，재CGF간가유효실현신식교호적전제하，장신식융합기술인입도반잠작전방진중；이용BP （Back Propagation）인공신경망락획취증거신식적기본치신분배，통과개진적D-S（Dempster-Shafer）증거이론대반잠CGF획취적신식진행종합，이차개진반잠CGF적이동책략。방진실험표명，재반잠CGF수잠과정중인입인공신경망락화신식융합기술，가유효제고CGF수잠적성공솔。
Since the Computer Generated Force ( CGF) can not take full advantage of battlefield information to optimize CGF submarine search strategy in the cooperative anti -submarine combat,the information fusion technology was introduced into the anti-submarine warfare simulation based on the effective interaction of the information between CGF .The basic confidence assignment of the evidence information was obtained using Back Propagation (BP) artificial neural network,and the information from antisubmarine CGF was synthesized by using the improved DS evidence theory .And thus the anti-submarine CGF mobile strategy was improved . Simulation results show that the introduction of artificial neural network and information fusion technology in antisubmarine CGF submarine search process can improve the anti -submarine efficiency .