基于“综合赋权”模糊物元模型的机场运行安全评价

为了保证机场运行安全,防止事故的发生,依据模糊物元分析理论,结合机场运行安全评价指标体系,构建了基于综合赋权的机场系统模糊物元安全评价模型。在该模型中,通过层次分析法和熵值法主客观综合所确定的权重,为指标体系进行线性加权,实现综合赋权,从而将计算得到的综合权重用于模糊物元建模与评价。实例分析结果表明,该模型步骤简单,过程科学合理,并兼顾了主客观因素的影响,评价结果总体反映了机场的真实安全水平,也为机场安全的科学评价提供了新思路。     

Single‐commodity stochastic network design under demand and topological uncertainties with insufficient data

Stochastic network design is fundamental to transportation and logistic problems in practice, yet faces new modeling and computational challenges resulted from heterogeneous sources of uncertainties and their unknown distributions given limited data. In this article, we design arcs in a network to optimize the cost of single‐commodity flows under random demand and arc disruptions. We minimize the network design cost plus cost associated with network performance under uncertainty evaluated by two schemes. The first scheme restricts demand and arc capacities in budgeted uncertainty sets and minimizes the worst‐case cost of supply generation and network flows for any possible realizations. The second scheme generates a finite set of samples from statistical information (e.g., moments) of data and minimizes the expected cost of supplies and flows, for which we bound the worst‐case cost using budgeted uncertainty sets. We develop cutting‐plane algorithms for solving the mixed‐integer nonlinear programming reformulations of the problem under the two schemes. We compare the computational efficacy of different approaches and analyze the results by testing diverse instances of random and real‐world networks. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 154–173, 2017     

Sensor placement in active multistatic sonar networks

The idea of deploying noncollocated sources and receivers in multistatic sonar networks (MSNs) has emerged as a promising area of opportunity in sonar systems. This article is one of the first to address point coverage problems in MSNs, where a number of points of interest have to be monitored in order to protect them from hostile underwater assets. We consider discrete “definite range” sensors as well as various diffuse sensor models. We make several new contributions. By showing that the convex hull spanned by the targets is guaranteed to contain optimal sensor positions, we are able to limit the solution space. Under a definite range sensor model, we are able to exclude even more suboptimal solutions. We then formulate a nonlinear program and an integer nonlinear program to express the sensor placement problem. To address the nonconvex single‐source placement problem, we develop the Divide Best Sector (DiBS) algorithm, which quickly provides an optimal source position assuming fixed receivers. Starting with a basic implementation of DiBS, we show how incorporating advanced sector splitting methods and termination conditions further improve the algorithm. We also discuss two ways to use DiBS to find multiple source positions by placing sensors iteratively or simultaneously. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 287–304, 2017     

From Nationalism to Factionalism: Faultlines in the Naga Insurgency

Do ceasefires or peace talks create fragmentation in the insurgent groups? Rather than proposing claims that can offer predictions about armed groups behaviour under ceasefires or peace processes, the analysts tend to focus largely on the dynamics between state and non-state actor. The experts pay little attention to overtime changes in social and local political context which might contribute to propelling a rebel group towards fragmentation and factionalism. The present study intends to fill this gap by exploring the shifting role of public opinion and ethnic support for the peace talks to ascertain whether it can increase the likelihood of factionalism in rebel groups or not. This article applies this approach to the case of Naga National Movement (1947–2015) in India, and finds that the proposed variable appears to have increased the frequency of factionalism in the movement.     

滑模控制的新型双幂次组合函数趋近律

提出一种基于双幂次组合函数趋近律的新型滑模控制方案。与现有的快速幂次或双幂次趋近律相比,具有更快的收敛速度,同时还保持了全局固定时间收敛特性,收敛时间上界与滑模初值无关。当系统存在有界扰动时,能够使滑模变量在有限时间内收敛到稳态误差界内,同时其稳态误差要小于现有方法的。仿真实验验证了该方法的有效性及理论分析的正确性。     

基于小弹性模量法的空间飞网构型优化设计

飞网构型设计对提高空间飞网系统的展开抓捕性能具有重要意义。用小弹性模量分析方法对空间飞网构型优化设计问题进行了研究。以绳网中内力分布均衡性为优化目标,选取飞网抛射过程中最大受力时刻为研究工况,赋予绳索单元极小弹性模量,进行静力学计算,并以变形后的结果为初始条件进行迭代分析。优化结果表明,绳网中的内力分布随迭代步数的增加而更趋于均匀。在不改变绳网拓扑结构的前提下,本文所建立的优化设计方法为空间飞网构型优化设计提供了一种参考途径。     

卫星导航抗干扰接收机信道大动态范围通用设计方法研究*

为适应“导航战”下的强干扰输入,导航接收机对模拟信道的动态范围提出了更高的要求。在给定的信噪比恶化容限约束下,原有的分析方法给出了二维曲线分析模型,得到了动态范围的优化设计及各级增益划分方法,但仅适用于输出功率基本不变的AGC电路。基于增加的AGC输出回退功率这一参数,论文提出了一种三维曲面求解模型,揭示了各电路参量与模拟信道动态范围的约束关系,可适用于输出功率变化的AGC电路,以实现更高的动态范围。针对三维模型中参数求解复杂的问题,利用纯衰减网络的特性将复杂的数值求解简化为直线求解,大幅降低了设计复杂度。在给出的设计实例中,动态范围测试结果与设计预期吻合较好,验证了方法的正确性。     

多核贝叶斯优化的模型决策树算法

构造模型决策树时超参数较多,参数组合复杂,利用网格搜索等调参方法将会消耗大量的时间,影响模型性能的提升。提出了一种多核贝叶斯优化的模型决策树算法,该算法为应对不同分类数据特性,采用三种高斯过程建模寻优,利用贝叶斯优化技术,选出最优的参数组合。实验结果表明,所提算法在参数寻优上要优于传统的模型决策树寻优方法,并且能够在迭代次数不多的情况下找到全局最优参数值,在一定程度上提升了算法的分类性能,节省了大量的调参时间。     

融合空间偏好和语义的个体活动识别方法

个体活动识别对用户画像、个性化推荐、异常行为检测、群体行为分析和基于活动的资源配置优化具有重要价值。提出了一种基于稀疏的社交媒体签到数据的个体活动语义识别方法,从签到数据中提取活动行为的时间周期性和趋势性特征,并采用空间偏好量化算法,从个体与群体活动的空间关联中提取群体和个体的空间访问偏好,使用自然语言嵌入工具BERT模型提取访问兴趣点的语义。时间特征、空间偏好特征和访问兴趣点名称语义特征共同构成表征群体、个体偏好的时空联合特征,通过极限梯度提升分类器对其进行分类,得到活动语义识别结果。在Foursquare数据集上的对比实验和消融实验中验证了所提活动语义识别模型可以有效提升活动语义识别的准确性。     

伞衣优化设计对群伞系统气动特性的影响分析

随着载人航天、深空探测等航天任务的蓬勃发展,航天器回收载荷质量大幅提高,以单具降落伞为功能核心的传统减速系统已不能满足大质量回收载荷日益提高的迫切要求,发展群伞减速着陆系统是实现大载重航天器高效减速和无损着陆要求的发展方向。本文采用数值模拟手段对群伞系统的气动特性开展仿真研究,结合环帆伞构型优化设计,分析了多种构型下群伞系统的气动特性。通过对仿真结果进行流场分析和数据对比发现,开窗/开缝设计既能够确保群伞系统具有良好的阻力特性,又能够维持群伞系统的工作稳定性,避免单伞之间由于受力而发生碰撞现象。采用数值仿真手段不仅可以提高降落伞研制效率,降低研发成本,也为设计人员掌握群伞系统的工作原理、促进降落伞设计理论发展提供了有力保证。