改进的二进制粒子群算法的传感器优化配置

传感器组合优化问题是设备状态检测系统设计的重要问题.在研究传感器与故障有向图的基础上,提出了传感器优化配置模型;根据传感器组合优化自身特点,从位改变率、惯性权重两个方面对BPSO算法进行了参数分析.结合免疫算法的“亲和度”思想以及非线性惯性权重递减公式,提出了改进的二进制粒子群算法.案例显示,改进的二进制PSO算法提高了算法在整个解空间的搜索能力,加快了收敛速度,能够很好地用于解决传感器优化问题.     

用于目标跟踪无线传感器网络的动态分簇算法

针对跟踪精度和网络能耗的问题,提出了一种用于目标跟踪无线传感器网络的基于预测的动态分簇算法.把目标运动过程看作是高斯马尔可夫过程,根据目标历史轨迹,估计下一时刻位置坐标和运动速度,然后基于估计结果优化选择分簇的簇头和簇成员,形成一个动态分簇来实现目标跟踪.仿真结果表明:该算法使目标跟踪有较好的跟踪精度,能有效均衡网络能耗,延长网络寿命.     

基于信息损失最小的预警卫星传感器调度模型

科学合理地调度预警卫星传感器资源是提高弹道导弹预警作战效能的重要手段.在预警卫星传感器资源(主要是凝视探测器)有限而进攻弹道导弹目标数量较多时,利用最小信息损失准则,将传感器调度问题转化为最优访问路径问题进行建模研究,满足了导弹预警资源调度的需要,仿真结果验证了模型的可靠性和可用性.     

A robust sensor covering and communication problem

We consider the problem of placing sensors across some area of interest. The sensors must be placed so that they cover a fixed set of targets in the region, and should be deployed in a manner that allows sensors to communicate with one another. In particular, there exists a measure of communication effectiveness for each sensor pair, which is determined by a concave function of distance between the sensors. Complicating the sensor location problem are uncertainties related to sensor placement, for example, as caused by drifting due to air or water currents to which the sensors may be subjected. Our problem thus seeks to maximize a metric regarding intrasensor communication effectiveness, subject to the condition that all targets must be covered by some sensor, where sensor drift occurs according to a robust (worst‐case) mechanism. We formulate an approximation approach and develop a cutting‐plane algorithm to solve this problem, comparing the effectiveness of two different classes of inequalities. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 582–594, 2015     

NSHT预警装备体系网络化建模与分析

针对NSHT的运动特性和NSHT预警装备网络化趋势,对NSHT情报的分布式碎片化的特点进行了分析,设计了装备体系节点间的信息流向。在此基础上,提出了基于复杂网络理论的NSHT预警装备体系网络模型,并对网络模型的拓扑结构、统计特征等进行了研究,提出了NSHT预警装备体系连接结构的设计建议和应用思路。     

FINANCIAL VERSUS HUMAN RESOURCES IN THE GREEK–TURKISH ARMS RACE 10 YEARS ON: A FORECASTING INVESTIGATION USING ARTIFICIAL NEURAL NETWORKS

This paper looks into the Greek–Turkish arms race a decade after an earlier contribution to the issue that relied heavily on artificial neural networks. The time period between the two papers contributes to the reliability of the results derived, not just by increasing the number of observations, but also mainly by incorporating the progress made in the realm of artificial intelligence. The focus on the case of both countries unlike the paper mentioned above that dealt with just the Greek side provides ample room for comparative purposes regarding the determinants of defense expenditure on both sides. The results derived in terms of input significance estimation support the findings of the earlier research as indicated above, pointing to the leading role of the demographic preponderance of Turkey over Greece. The paper also points to the fact that 10 years later, Turkey continues to set the arms race rules against its rival by determining the defense expenditure of Greece, whereas the role of the latter in affecting the military spending of Turkey is non‐existent.     

基于能量均衡的无线传感器网络生命周期延长策略

为了从能量均衡角度出发解决无线传感器网络生命周期延长问题,从而延长整个物联网生命周期,针对无线传感器网络节点遭遇"路由空洞"的时候出现路由中断和生命周期缩短现象,分析能量消耗原理,构建最优跳数模型和能量均衡协议,并提出采用能量均衡的思路减少节点能量消耗。实验仿真发现,应用能量均衡协议使无线传感器网络节点能量分布更加均匀,节点能量消耗时间明显变长,而个别节点能量消耗速度明显大于其他节点的情况得以减少,达到延长无线传感器网络生命周期的目的。仿真结果验证了该方法的可行性。     

利用循环网络的降落伞开伞载荷补偿方法

为了对降落伞充气展开过程中的开伞载荷进行更加准确的预测,提出一种基于循环神经网络的开伞载荷补偿计算方法,包括模型架构和数据处理方式。该方法将充气时间法计算的预测值代入循环网络进行二次计算,使最终结果能够更加贴近试验真值。使用多层前馈网络、标准循环网络与长短时记忆网络三种网络进行比较,验证了所提模型预测结果的适用性和准确性,研究了学习率、输入层维度和隐层维度等超参数对模型性能的影响,并给出了基于长短时记忆网络的补偿模型最优训练条件。实验结果表明,利用循环网络进行开伞载荷预测具有较好的拟合结果,为机器学习与降落伞工业的学科交叉研究提供了一定的参考方向。     

采用无线携能技术的中继辅助CR-NOMA系统能效分析

针对现有关于认知无线电非正交多址接入网络的研究中终端电池容量有限和能源利用率低的缺点,采用了中继辅助用户进行传输,并且引入无线信息和能量同时传输的方式。在用户服务质量和最小能量捕获的约束条件下推导了次用户传输能效表达式,通过分式规划方法把非凸的目标函数转化为优化中继发射功率、中继功率分配和接收端功率分配三个凸的单目标问题,并分别用函数单调性、黄金分割算法、拉格朗日对偶算法和多目标联合优化算法进行优化,求得了全局最优解,使次用户系统传输能效最大化。对所采用的算法复杂度进行分析,仿真结果表明:与传统的正交多址接入方案相比较,在提高系统频谱利用率的同时,次用户传输能效有47%的提高。     

一种基于最小生成树的无线多跳网络信道分配算法

为提高无线多跳网络的吞吐量和传输可靠性,提出一种信道分配算法。该算法优先考虑最小生成树上的可用信道,为每个节点分配信道资源;然后考虑利用生成树外其他可用链路,为节点提供信道资源,以提高吞吐量。算法通过考虑每个用户的通信需求,可以充分利用空闲信道资源。仿真结果显示,相比于不考虑最小生成树外链路时,有效地提高了网络整体吞吐量。