提出了用动态影响网(Dynamic Influence Nets,DINs)对指挥控制(Command and Control,C2)组织行动过程(Course of Actions,COA)问题进行建模的方法。该方法通过引入因果强度参数,替代了传统动态贝叶斯网络中的条件概率表。给出了利用因...提出了用动态影响网(Dynamic Influence Nets,DINs)对指挥控制(Command and Control,C2)组织行动过程(Course of Actions,COA)问题进行建模的方法。该方法通过引入因果强度参数,替代了传统动态贝叶斯网络中的条件概率表。给出了利用因果强度参数进行概率传播的具体计算方法。结合一个联合作战的仿真算例,验证了该建模方法的优越性和有效性。展开更多
The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The con...The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The connecting structure of combat entities in it is of great importance for supporting the normal process of the system. In this paper, we explore the optimizing strategy of the structure of the anti-aircraft network by establishing extra communication channels between the combat entities.Firstly, the thought of combat network model(CNM) is borrowed to model the anti-aircraft system as a heterogeneous network. Secondly, the optimization objectives are determined as the survivability and the accuracy of the system. To specify these objectives, the information chain and accuracy chain are constructed based on CNM. The causal strength(CAST) logic and influence network(IN) are introduced to illustrate the establishment of the accuracy chain. Thirdly, the optimization constraints are discussed and set in three aspects: time, connection feasibility and budget. The time constraint network(TCN) is introduced to construct the timing chain and help to detect the timing consistency. Then, the process of the multi-objective optimization of the structure of the anti-aircraft system is designed.Finally, a simulation is conducted to prove the effectiveness and feasibility of the proposed method. Non-dominated sorting based genetic algorithm-Ⅱ(NSGA2) is used to solve the multiobjective optimization problem and two other algorithms including non-dominated sorting based genetic algorithm-Ⅲ(NSGA3)and strength Pareto evolutionary algorithm-Ⅱ(SPEA2) are employed as comparisons. The deciders and system builders can make the anti-aircraft system improved in the survivability and accuracy in the combat reality.展开更多
储粮害虫是影响粮食安全的重要因素,深入研究储粮害虫事件的发展过程及其因果关系极为关键。通过量化分析储粮害虫事件之间的因果强度,能够更加准确地评估潜在风险,帮助相关工作人员制定防控措施,减少不必要的损失。为解决储粮害虫领域...储粮害虫是影响粮食安全的重要因素,深入研究储粮害虫事件的发展过程及其因果关系极为关键。通过量化分析储粮害虫事件之间的因果强度,能够更加准确地评估潜在风险,帮助相关工作人员制定防控措施,减少不必要的损失。为解决储粮害虫领域数据中存在的数据偏差而造成模型过分依赖数据集中的表面特征,在应对泛化数据时效果不佳的问题,该研究提出一种反事实数据增强的因果强度计算方法,旨在准确量化事件之间的因果强度。设计了一个反事实数据增强的因果强度计算框架(counterfactual data augmentation-event causal strength,CDA-ECS),通过利用大语言模型(large language model,LLM)生成反事实实例,对原始数据进行扩展,将去偏的因果知识整合进预训练语言模型中,帮助其更深入地理解和学习句子的因果关系,提高模型的泛化能力。在公共数据集和领域数据集上的试验表明,所提方法能够训练出更加稳健的模型,在领域泛化数据的推理任务上准确率提高了2.4个百分点,能有效应用于储粮害虫事件的因果强度计算。在储粮害虫领域,反事实数据增强方法的引入为解决数据偏差提供了一种新的视角,增强后数据的多样性和复杂性使得模型能够更加深入地理解害虫行为与环境因素之间的复杂联系,进一步帮助实现储粮害虫事件的风险分析。该研究证明了反事实数据增强方法的可行性和有效性,为实现储粮害虫事件的因果强度计算提供了一定的参考。展开更多
文摘提出了用动态影响网(Dynamic Influence Nets,DINs)对指挥控制(Command and Control,C2)组织行动过程(Course of Actions,COA)问题进行建模的方法。该方法通过引入因果强度参数,替代了传统动态贝叶斯网络中的条件概率表。给出了利用因果强度参数进行概率传播的具体计算方法。结合一个联合作战的仿真算例,验证了该建模方法的优越性和有效性。
基金supported by the National Natural Science Foundation of China(72071206).
文摘The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The connecting structure of combat entities in it is of great importance for supporting the normal process of the system. In this paper, we explore the optimizing strategy of the structure of the anti-aircraft network by establishing extra communication channels between the combat entities.Firstly, the thought of combat network model(CNM) is borrowed to model the anti-aircraft system as a heterogeneous network. Secondly, the optimization objectives are determined as the survivability and the accuracy of the system. To specify these objectives, the information chain and accuracy chain are constructed based on CNM. The causal strength(CAST) logic and influence network(IN) are introduced to illustrate the establishment of the accuracy chain. Thirdly, the optimization constraints are discussed and set in three aspects: time, connection feasibility and budget. The time constraint network(TCN) is introduced to construct the timing chain and help to detect the timing consistency. Then, the process of the multi-objective optimization of the structure of the anti-aircraft system is designed.Finally, a simulation is conducted to prove the effectiveness and feasibility of the proposed method. Non-dominated sorting based genetic algorithm-Ⅱ(NSGA2) is used to solve the multiobjective optimization problem and two other algorithms including non-dominated sorting based genetic algorithm-Ⅲ(NSGA3)and strength Pareto evolutionary algorithm-Ⅱ(SPEA2) are employed as comparisons. The deciders and system builders can make the anti-aircraft system improved in the survivability and accuracy in the combat reality.
文摘储粮害虫是影响粮食安全的重要因素,深入研究储粮害虫事件的发展过程及其因果关系极为关键。通过量化分析储粮害虫事件之间的因果强度,能够更加准确地评估潜在风险,帮助相关工作人员制定防控措施,减少不必要的损失。为解决储粮害虫领域数据中存在的数据偏差而造成模型过分依赖数据集中的表面特征,在应对泛化数据时效果不佳的问题,该研究提出一种反事实数据增强的因果强度计算方法,旨在准确量化事件之间的因果强度。设计了一个反事实数据增强的因果强度计算框架(counterfactual data augmentation-event causal strength,CDA-ECS),通过利用大语言模型(large language model,LLM)生成反事实实例,对原始数据进行扩展,将去偏的因果知识整合进预训练语言模型中,帮助其更深入地理解和学习句子的因果关系,提高模型的泛化能力。在公共数据集和领域数据集上的试验表明,所提方法能够训练出更加稳健的模型,在领域泛化数据的推理任务上准确率提高了2.4个百分点,能有效应用于储粮害虫事件的因果强度计算。在储粮害虫领域,反事实数据增强方法的引入为解决数据偏差提供了一种新的视角,增强后数据的多样性和复杂性使得模型能够更加深入地理解害虫行为与环境因素之间的复杂联系,进一步帮助实现储粮害虫事件的风险分析。该研究证明了反事实数据增强方法的可行性和有效性,为实现储粮害虫事件的因果强度计算提供了一定的参考。
