作战网络能够加速作战体系中杀伤链的闭合从而倍增作战效果,但是其也面临着被重点毁伤的威胁,为快速有效恢复甚至提升作战网络的鲁棒性,对作战网络级联失效建模和鲁棒性恢复方法展开了研究。首先,针对作战网络建模存在偏差的问题,从实...作战网络能够加速作战体系中杀伤链的闭合从而倍增作战效果,但是其也面临着被重点毁伤的威胁,为快速有效恢复甚至提升作战网络的鲁棒性,对作战网络级联失效建模和鲁棒性恢复方法展开了研究。首先,针对作战网络建模存在偏差的问题,从实际出发构建了双层异质群依赖作战网络模型,然后分析并设计了条件性群依赖失效、非连通失效和临界过载失效等级联失效过程,并提出具有作战意义的网络鲁棒性指标。考虑到时效性和恢复资源的限制,利用作战网络节点的属性特征,提出一种基于容量和重要性的边界节点优先恢复(prior recovery based on capacity and importance,PRCI)方法。最后,通过不同方法对比、调整模型参数等仿真实验检验所提方法的有效性和可行性。仿真结果表明,PRCI方法的恢复效果明显优于其他基准方法,具有起效快,迭代少的特点,在相同资源条件下可快速有效恢复作战网络的能力;同时还发现该方法的恢复效果与容忍度、容量参数、过载承受系数及恢复比例成正比,与负载参数成反比,进一步为作战网络的结构优化设计提供了参考。展开更多
The tell tail is usually placed on the triangular sail to display the running state of the air flow on the sail surface.It is of great significance to make accurate judgement on the drift of the tell tail of the sailb...The tell tail is usually placed on the triangular sail to display the running state of the air flow on the sail surface.It is of great significance to make accurate judgement on the drift of the tell tail of the sailboat during sailing for the best sailing effect.Normally it is difficult for sailors to keep an eye for a long time on the tell sail for accurate judging its changes,affected by strong sunlight and visual fatigue.In this case,we adopt computer vision technology in hope of helping the sailors judge the changes of the tell tail in ease with ease.This paper proposes for the first time a method to classify sailboat tell tails based on deep learning and an expert guidance system,supported by a sailboat tell tail classification data set on the expert guidance system of interpreting the tell tails states in different sea wind conditions,including the feature extraction performance.Considering the expression capabilities that vary with the computational features in different visual tasks,the paper focuses on five tell tail computing features,which are recoded by an automatic encoder and classified by a SVM classifier.All experimental samples were randomly divided into five groups,and four groups were selected from each group as the training set to train the classifier.The remaining one group was used as the test set for testing.The highest resolution value of the ResNet network was 80.26%.To achieve better operational results on the basis of deep computing features obtained through the ResNet network in the experiments.The method can be used to assist the sailors in making better judgement about the tell tail changes during sailing.展开更多
针对攻击代价相等时的有限资源网络毁伤问题,给出了网络毁伤最大化的定义。为了改进近似求解算法求解毁伤最大化问题时复杂度较高的缺陷,提出了基于拓扑势和CELF(cost-effective lazy-forward)的TPCELF(algorithm based on topology pot...针对攻击代价相等时的有限资源网络毁伤问题,给出了网络毁伤最大化的定义。为了改进近似求解算法求解毁伤最大化问题时复杂度较高的缺陷,提出了基于拓扑势和CELF(cost-effective lazy-forward)的TPCELF(algorithm based on topology potential and CELF)算法。利用无标度网络和实测网络进行实验,结果表明,TPCELF算法在计算速度上有较大的提升,网络平均毁伤效果接近于近似求解算法;且优于采用常见重要性度量指标排序算法得到的平均毁伤效果。所提方法可从网络毁伤的角度为复杂网络关键节点挖掘提供参考。展开更多
文摘利用改进的渗透装置试验研究了细颗粒(0.075~1 mm)含量相同时骨架颗粒组成含量不同对散粒土的管涌发生临界条件以及颗粒侵蚀流失规律的影响,结果表明:不同颗粒级配的试样在管涌发生前,水力梯度与渗流速度呈线性关系,基本符合达西定律;骨架颗粒1~2、2~3、3~5 mm 3个粒径段对管涌发展起到了阻碍作用,其中1~2 mm粒径段颗粒对管涌孔隙的堵塞作用强于另外两个粒径段颗粒;对于不同级配的骨架颗粒,其不均匀系数越大,试样的下限临界水力梯度值就越大,细颗粒越不易起动,发生管涌的时间越晚,而不同级配的骨架颗粒对试样的上限临界水力梯度影响较小。
文摘作战网络能够加速作战体系中杀伤链的闭合从而倍增作战效果,但是其也面临着被重点毁伤的威胁,为快速有效恢复甚至提升作战网络的鲁棒性,对作战网络级联失效建模和鲁棒性恢复方法展开了研究。首先,针对作战网络建模存在偏差的问题,从实际出发构建了双层异质群依赖作战网络模型,然后分析并设计了条件性群依赖失效、非连通失效和临界过载失效等级联失效过程,并提出具有作战意义的网络鲁棒性指标。考虑到时效性和恢复资源的限制,利用作战网络节点的属性特征,提出一种基于容量和重要性的边界节点优先恢复(prior recovery based on capacity and importance,PRCI)方法。最后,通过不同方法对比、调整模型参数等仿真实验检验所提方法的有效性和可行性。仿真结果表明,PRCI方法的恢复效果明显优于其他基准方法,具有起效快,迭代少的特点,在相同资源条件下可快速有效恢复作战网络的能力;同时还发现该方法的恢复效果与容忍度、容量参数、过载承受系数及恢复比例成正比,与负载参数成反比,进一步为作战网络的结构优化设计提供了参考。
基金supported by the Shandong Provin-cial Key Research Project of Undergraduate Teaching Reform(No.Z2022218)the Fundamental Research Funds for the Central University(No.202113028)+1 种基金the Graduate Education Promotion Program of Ocean University of China(No.HDJG20006)supported by the Sailing Laboratory of Ocean University of China.
文摘The tell tail is usually placed on the triangular sail to display the running state of the air flow on the sail surface.It is of great significance to make accurate judgement on the drift of the tell tail of the sailboat during sailing for the best sailing effect.Normally it is difficult for sailors to keep an eye for a long time on the tell sail for accurate judging its changes,affected by strong sunlight and visual fatigue.In this case,we adopt computer vision technology in hope of helping the sailors judge the changes of the tell tail in ease with ease.This paper proposes for the first time a method to classify sailboat tell tails based on deep learning and an expert guidance system,supported by a sailboat tell tail classification data set on the expert guidance system of interpreting the tell tails states in different sea wind conditions,including the feature extraction performance.Considering the expression capabilities that vary with the computational features in different visual tasks,the paper focuses on five tell tail computing features,which are recoded by an automatic encoder and classified by a SVM classifier.All experimental samples were randomly divided into five groups,and four groups were selected from each group as the training set to train the classifier.The remaining one group was used as the test set for testing.The highest resolution value of the ResNet network was 80.26%.To achieve better operational results on the basis of deep computing features obtained through the ResNet network in the experiments.The method can be used to assist the sailors in making better judgement about the tell tail changes during sailing.
文摘针对攻击代价相等时的有限资源网络毁伤问题,给出了网络毁伤最大化的定义。为了改进近似求解算法求解毁伤最大化问题时复杂度较高的缺陷,提出了基于拓扑势和CELF(cost-effective lazy-forward)的TPCELF(algorithm based on topology potential and CELF)算法。利用无标度网络和实测网络进行实验,结果表明,TPCELF算法在计算速度上有较大的提升,网络平均毁伤效果接近于近似求解算法;且优于采用常见重要性度量指标排序算法得到的平均毁伤效果。所提方法可从网络毁伤的角度为复杂网络关键节点挖掘提供参考。
