Network analysis of Chinese air transport delay propagation

The Chinese air transport system has witnessed an important evolution in the last dec-ade, with a strong increase in the number of flights operated and a consequent reduction of their punctuality. In this contribution, we propose modelling the process of delay propagation by using complex networks, in which nodes are associated to airports, and links between pairs of them are assigned when a delay propagation is detected. Delay time series are analysed through the well-known Granger Causality, which allows detecting if one time series is causing the dynamics observed in a second one. Results indicate that delays are mostly propagated from small and regio-nal airports, and through flights operated by turbo-prop aircraft. These insights can be used to design strategies for delay propagation dampening, as for instance by including small airports into the system's Collaborative Decision Making.     

基于神经网络的仿真转台控制系统

在转台存在偏载、摩擦等不确定负载干扰的情况下,用神经网络与PID(Proportional-Integral-Differential)控制相结合的方法,设计了适应负载变化的转台控制系统.分析了基于BP(Back Propagation)神经网络的自适应PID控制器的基本原理,建立了转台位置控制系统的数学模型,并对控制系统进行仿真分析和实验验证,通过与传统PID控制的对比实验与仿真表明:所设计系统由于有自学习能力,能动态调整PID参数,使系统表现出良好的抗干扰能力和跟踪性能,证明了所设计系统的有效性.该算法结构简单,PID初始参数调整方便,易于在转台实时控制系统中应用.     

分数阶Hopfield型神经网络的全局渐近稳定性

研究了分数阶Hopfield型神经网络的全局渐近稳定性,通过LMI方法得到了一种实现系统全局渐近稳定性的LMI形式条件,通过实例仿真验证了结论的正确性。     

贝叶斯网络在飞控系统可靠性评估中的应用

把一种基于贝叶斯网络的故障树分析法应用于飞控系统俯仰控制功能的可靠性评估中,突破传统故障树分析法的局限性——各部件独立、状态为二值,不但可以计算系统的可靠性指标,而且可以定量给出某个事件或某几个事件在系统可靠性中所占的地位,找出系统的薄弱环节。     

Neural network development for the forecasting of upper atmosphere parameter distributions

This paper presents a neural network modeling approach to forecast electron concentration distributions in the 150–600 km altitude range above Arecibo, Puerto Rico. The neural network was trained using incoherent scatter radar data collected at the Arecibo Observatory during the past two decades, as well as the Kp geomagnetic index provided by the National Space Science Data Center. The data set covered nearly two solar cycles, allowing the neural network to model daily, seasonal, and solar cycle variations of upper atmospheric parameter distributions. Two types of neural network architectures, feedforward and Elman recurrent, are used in this study. Topics discussed include the network design, training strategy, data analysis, as well as preliminary testing results of the networks on electron concentration distributions.     

A New Exposed-terminal-free MAC Protocol for Multi-hop Wireless Networks

This article presents a new multichannel medium access control (MAC) protocol to solve the exposed-terminal (ET) problem for efficient channel sharing in multi-hop wireless networks. It uses request-to-send and clear-to-send (RTS/CTS) dialogue on a common channel and flexibly opts for conflict-free traffic channels to carry out the data packet transmission on the basis of a new channel selection scheme. The acknowledgment (ACK) packet for the data packet transmission is sent back to the sender over another common channel thus completely eliminating the exposed-terminal effects. Any adjacent communication pair can take full advantage of multiple traffic channels without collision and the spatial reuse of the same channel is extended to other communication pairs which are even within 2 hops from them. In addition, the hidden-terminal effect is also considerably reduced because most of possible packet collisions on a single channel are avoided due to traffic load balance on multichannels. Finally, a performance comparison is made between the proposed protocol and other typical MAC protocols. Simulation results evidence its obvious superiority to the MAC protocols associated with other channel selection schemes and traditional ACK transmission scheme as well as cooperative asynchronous multichannel MAC (CAM-MAC) protocol in terms of four performance indices: total channel utilization, average channel utilization, average packet delay, and packet dropping rate.     

FDDI令牌环与SAE线性令牌总线的比较研究

分布式分牌传递网络将进入高速实时的航空电子通信系统。本文针对两种典型的令牌传递网络，即美国自动化工程学会（SAE）的线性令牌传递总线（LTPB）与美国国家标准协会（ANSI）的分布式光纤数据接口（FDDI）令牌环进行了各个方面的比较研究，最后给出了比较分析结论。     

基于多个前向神经网络和遗传算法的边界检测法

本文提出了一种基于前向神经网络和遗传算法的图象边界检测方法,这种方法由多个三层子前向神经网络并置连接加一个ＭＡＸＮＥＴ子神经网络形成,每个前向神经子网络的隐含层神经元个数和所有人权重系数由遗传算法优化确定,实验结果表明,本文提出了这咱边界检测方法抗噪声能力强,检测到的这界位置更为准确。     

网络化战争中的复杂网络拓扑建模

网络化战争中网络拓扑模型的构建是利用复杂网络理论研究网络化战争的基础。本文根据网络化战争的特点,从复杂网络动力学角度,对BA模型进行扩展,通过在节点分类和连接规则两方面增添假设,构建了网络化战争中的复杂网络拓扑模型。仿真结果表明,在该演化规则下生成的网络具有无尺度和小世界特性。对网络模型抗毁性的研究为网络化战争中攻击节点的选择及网络的构建和改进提供理论依据。     

Mobility control of unmanned aerial vehicle as communication relay in airborne multi-user systems

In this paper, a model-based adaptive mobility control method for an Unmanned Aerial Vehicle(UAV) acting as a communication relay is presented, which is intended to improve the network performance in airborne multi-user systems. The mobility control problem is addressed by jointly considering unknown Radio Frequency(RF) channel parameters, unknown multi-user mobility, and non-available Angle of Arrival(AoA) information of the received signal. A Kalman filter and a least-square-based estimation algorithm are used to predict the future user positions and estimate the RF channel parameters between the users and the UAV, respectively. Two different relay application cases are considered: end-to-end and multi-user communications. A line search algorithm is proposed for the former, with its stability given and proven, whereas a simplified gradient-based algorithm is proposed for the latter to provide a target relay position at each decision time step, decreasing the two-dimensional search to a one-dimensional search. Simulation results show that the proposed mobility control algorithms can drive the UAV to reach or track the optimal relay position movement, as well as improving network performance. The proposed method reflects the properties of using different metrics as objective network performance functions.