Analysis of air traffic control operational impact on aircraft vertical profiles supported by machine learning

The Air Traffic Management system is under a paradigm shift led by NextGen and SESAR. The new trajectory-based Concept of Operations is supported by performance-based trajectory predictors as major enablers. Currently, the performance of ground-based trajectory predictors is affected by diverse factors such as weather, lack of integration of operational information or aircraft performance uncertainty.Trajectory predictors could be enhanced by learning from historical data. Nowadays, data from the Air Traffic Management system may be exploited to understand to what extent Air Traffic Control actions impact on the vertical profile of flight trajectories.This paper analyses the impact of diverse operational factors on the vertical profile of flight trajectories. Firstly, Multilevel Linear Models are adopted to conduct a prior identification of these factors. Then, the information is exploited by trajectory predictors, where two types are used: point-mass trajectory predictors enhanced by learning the thrust law depending on those factors; and trajectory predictors based on Artificial Neural Networks.Air Traffic Control vertical operational procedures do not constitute a main factor impacting on the vertical profile of flight trajectories, once the top of descent is established. Additionally, airspace flows and the flight level at the trajectory top of descent are relevant features to be considered when learning from historical data, enhancing the overall performance of the trajectory predictors for the descent phase.     

人工智能在舰船避碰领域的应用

讨论人工智能技术的分类,分析模糊逻辑、神经网络(模糊神经网络)、专家系统、主体(A-gent)和基于案例推理(CBR)技术等各种人工智能技术在避碰领域的研究现状,展望了人工智能技术在避碰领域的发展前景.     

变权值加快收敛的路径寻优实时算法

为获得满意解为目标的最优路径选择问题，给出了一种加权的LRTA^*(Learning Real-TimeA^*)算法，通过改变估价函数值更新规则与解时间和解质量的相对折中，加快算法收敛速度。实例应用表明，该方法比LRTA^*算法更快地收敛于满意解，是一种求解大城市稠密路网两点间最优路径的有效方法。     

基于知识的智能CAD系统设计

通过对工程智能ＣＡＤ系统及其设计模型的研究,提出了工程智能ＣＡＤ系统设计理论;规划控制下的二阶段设计理论,论述了基于这一理论的工程智能ＣＡＤ系统设计方法、设计对象的模型构造方法和智能ＣＡＤ系统中各类工程设计知识的应用。并已将这一方法成功地应用于工程智能ＣＡＤ系统的开发实践。     

习题库与指导方法模型的设计与实现

本文研究了智能计算机辅助教学系统中习题库的实现方法，智能指导方式的设计思想及状态信息数据加密解密的保存。     

铁路基础设施全寿命检测技术与发展

铁路基础设施检测是铁路安全运行的保障和科学指导线路养护维修的重要依据,对我国铁路发展和长期安全运营具有重要意义。本文系统地介绍了铁路基础设施全寿命周期内联调联试阶段和运营阶段检测技术的创新与发展,以及对海量检测监测数据的分析运用。提出了基础设施检测监测技术发展方向,如检测装备统型融合和智能化发展、检测数据管理和分析共享平台建设、基础设施多源数据智能分析应用等,对完善我国铁路基础设施检测体系起到重要指引作用。     

基于人工神经网络的车次追踪算法研究

在高速铁路运营调度系统中,对列车进行跟踪,实时获取准确的列车车次号是必不可少的。车次追踪主要包括原始车次号的获取、车次号的逻辑追踪处理和列车车次校核3个方面。逻辑追踪是在某一时刻和某一地点,根据列车的实际运行情况,自动推算当时运行或者停车的列车的车次号。车次校核是根据计划或无线等车次号对追踪结果进行校核。基于人工神经网络算法的车次追踪技术,快速、有效,可以避免由于轨道电路故障而引起的车次追踪错误。     

智能低压配电系统在地铁中的应用

根据地铁低压配电系统的特点,结合当前智能低压系统的广泛应用,提出了地铁智能低压的基本组成、功能要求、实现方法以及发展方向.智能化低压系统总的发展趋势是智能化、网络化、组合化、模块化、高性能和小型化,并将电力、电子、计算机、信息神经网络及模糊控制等相关的高新技术有机结合,提高整个配电系统的可靠性.     

Practicability study on the suitability of artificial,neural networks for the approximation of unknown steering torques

For steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.     

基于视频的车辆特征表达与分类算法

为实现车辆类型的高精度检测,提出了基于偏心矩向量的特征表达方法,将运动车辆轮廓点与重心之间的距离定义为偏心矩,构造特征向量实现车辆的标识.该特征向量具备旋转、平移、伸缩的不变性,能够克服目标运动状态和环境变化的影响.采用支持向量机构建多类最优分类超平面,实现运动车辆的多类别快速分类.实验结果表明,不同类别车辆特征区分明显,识别准确率可达94%以上.