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基于证据网络的装备体系贡献率评估方法研究
引用本文:游雅倩,姜江,孙建彬,赵丹玲,杨克巍. 基于证据网络的装备体系贡献率评估方法研究[J]. 系统工程与电子技术, 2019, 41(8): 1780-1788. DOI: 10.3969/j.issn.1001-506X.2019.08.15
作者姓名:游雅倩  姜江  孙建彬  赵丹玲  杨克巍
作者单位:国防科技大学系统工程学院, 湖南 长沙 410073
基金项目:国家自然科学基金(71571185,71671186)资助课题
摘    要:体系贡献率评估是装备体系发展规划中一项重要内容。针对装备体系贡献率评估中存在的体系结构复杂、评估信息不确定性强等特点,提出了基于证据网络的装备体系贡献率评估方法。该方法依据专家经验构建网络模型与置信规则库,在此基础上通过证据推理算法对不同装备体系的作战效能进行分析,进而实现装备体系贡献率的评估。最后,以外军典型联合登岛作战装备体系为例验证了所提出方法的可行性。该方法能够为装备体系需求论证、体系发展规划等国防军事领域重大决策提供支撑。

关 键 词:装备体系  作战效能  贡献率评估  证据网络

Evidential network-based evaluation method of contribution toweapon system-of-systems
YOU Yaqian,JIANG Jiang,SUN Jianbin,ZHAO Danling,YANG Kewei. Evidential network-based evaluation method of contribution toweapon system-of-systems[J]. System Engineering and Electronics, 2019, 41(8): 1780-1788. DOI: 10.3969/j.issn.1001-506X.2019.08.15
Authors:YOU Yaqian  JIANG Jiang  SUN Jianbin  ZHAO Danling  YANG Kewei
Affiliation:College of Systems Engineering, National University of Defense Technology, Changsha 410073, China;
Abstract:System-of-systems contribution evaluation is an important part of the development of weapon system construction. The system-of-systems contribution’s connotation and characteristics are analyzed, such as the complex structure of the system and uncertainty information. A contribution evaluation approach for weapon system-of-systems based on evidential network is proposed to address these challenges. The network structure model and belief rule base according to the experience of specialists are built. On this basis, the rule based inference methodology is used to infer the operational efficiency for different weapon system of systems. Finally, a case study of joint landing campaign weapon system-of-systems is conducted based on the typical foreign weapon to verify the feasibility of the proposed approach. This approach can support decision-making in the fields of national defense, such as the argumentation of weapon demanding and the programming of system development.
Keywords:weapon system-of-systems   operational effectiveness   contribution evaluation   evidential network  
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