不确定信息下考虑相关性与多样性的作战方案推荐方法

Combat plans recommendation method considering relativity and diversity under uncertain information

针对现有的作战需求表征与作战方案评价存在不确定性信息、作战方案设计中经验积累与重用以及作战方案推荐中相关性与多样性权衡问题,提出了一种不确定信息下考虑相关性与多样性的作战方案推荐方法。首先,将粗糙集理论融入最优最劣法(best-worst method,BWM)中对各作战能力属性进行赋权;其次,给出了不确定信息下作战方案与任务需求之间的相关性、作战方案之间的多样性计算模型;然后,提出了权衡相关性和多样性的行列式点过程(determinantal point process,DPP)模型,在此基础上,给出了贪婪最大后验概率(maximum a posterior,MAP)推断算法和贪婪Trade-off推断算法以获得作战方案最优推荐子集;最后,通过案例分析验证了所提模型和方法的适用性和可行性。

There are uncertainty information,experience accumulation and reuse in operation plan design,and the trade-off between relativity and diversity in operation plan recommendation.An operational plan recommendation method considering relativity and diversity under uncertain information is proposed.Firstly,the rough set theory is integrated into the best-worst method(BWM)to weight each combat capability attribute.Secondly,the relativity between operational plan and mission requirements under uncertain information and the diversity calculation model between operational plan are given.Then,a determinant point process(DPP)model is proposed to balance relativity and diversity.On this basis,greedy maximum a posterior(MAP)inference algorithm and greedy Trade-off inference algorithm are given to obtain the best recommended subset of operational plan.Finally,the applicability and feasibility of the proposed model and method are verified by case study.