接触网检测车数据处理软件

本文通过分析接触网检测车数据处理系统的数据流向，数据组成及工作过程，确定了软件结构，软件功能及数据结构，同时讨论了软件设计中所采取的主要技术。     

现代船舶动力定位系统设计

围绕现代动力定位系统的设计问题,讨论系统的构建、数学建模、控制器设计和推力器的推力分配,重点给出了基于扩展Kalman滤波的动力定位LQG控制器设计算法。     

基于闭环力反馈原理的非线性液压主动阻尼悬架模型的研究及优化设计

本文在理论上建立了一套基于主动力反馈原理的新型主动阻尼悬架的设计和优化方法。首先提出了该主动阻尼悬架的实现模型，该模型是在传统的液力减振器的基础上，应用半主动控制的思想，结合力反馈的原理建立起来的内部液压反馈阻尼网络模型。理论优化分析和计算机仿真表明，通过该液阻网络模型，即可以实现电控的主动阻尼悬架的功能，它可以根据汽车行驶路况的好坏，自适应地调节悬架阻尼大小以实现主动阻尼悬架的最优控制。     

Simulation studies of information propagation in a self-organizing distributed traffic information system

This paper investigates the feasibility of a self-organizing, completely distributed traffic information system based upon vehicle-to-vehicle communication technologies. Unlike centralized traffic information systems, the proposed system does not need public infrastructure investment as a prerequisite for implementation. Due to the complexity of the proposed system, simulation is selected as the primary approach in the feasibility studies. A simulation framework is built based on an existing microscopic traffic simulation model for the simulation studies. The critical questions for building the proposed market-driven system are examined both from communication requirements and traffic engineering points of view. Traffic information propagation both in freeway and arterial networks via information exchange among IVC-equipped vehicles is tested within the simulation framework. Results on the probability of successful IVC and traffic information propagation distance obtained from the simulation studies are generated and analyzed under incident-free and incident conditions for various roadway formats and parameter combinations. Comparisons between the speed of the incident information wave and the speed of the corresponding traffic shock wave due to the incident are analyzed for different scenarios as the most crucial aspect of the information propagation as a potential foundation for application in such a decentralized traffic information system.     

人工神经网络在故障诊断系统中的应用

人工神经网络以其独到的联想、记忆、储存和学习功能，在故障诊断领域受到了广泛关注。其中，BP网络是最成熟、应用最广泛的一种网络。但BP网络在实际应用中也存在诸多不足，如学习率的取值需要凭借经验或试算选取，网络学习收敛速度慢以及易陷入局部最小点等。针对BP网络的这些不足，采用了Rumelhan附加惯性冲量和动态调整学习率相结合的改进的BP网络方法，并尝试用该改进算法来对凝汽器进行故障诊断。事实证明，在平均情况下，本系统收敛速度远远快于基本的BP算法。     

专用铁路综合数据通信网建设方案探讨

铁路综合数据通信网,是铁路信息化建设的基础平台,建设时首先应完善铁路基础通信网,然后从业务需求、网络结构、技术方案、网络管理、安全策略等几个方面综合考虑,合理规划,有效实现资源最大化的目标,使专用铁路信息化建设更科学、更合理。     

平行调试方法的应用及安全风险分析

为了避免综合监控系统延伸线接入主线时功能调试对主线运营造成的影响,通过在主线停运期间用增设的临时中央级设备进行调试,在主线运营期间则恢复至原有中央级设备,当调试已完成且相应问题已基本整改时将延伸线正式接入主线。将其中搭建的临时中央级设备、延伸线临时接入主线、开展平行调试、骨干网接入和设备升级等重要步骤进行归纳总结,并针对项目实施前的主线通信网络发生功能性损害的安全风险,以及项目实施过程中的系统数据库出现紊乱、临时设备上电后超载跳闸、非调试期间人员误操作等的安全风险提出相应管控措施,进一步提高后续类似项目的施工效率和安全性。     

用改进的前向神经网络预测铁路货运量

对影响铁路货运量的因素进行了分析。根据影响铁路货运量的诸因素的特点，介绍了一种改进的前向神经网络预测方法，并建立了铁路货运量前向神经网络预测模型。算例表明，其预测精度高于常规预测方法。     

Hub location with flow economies of scale

A characteristic feature of hub and spoke networks is the bundling of flows on the interhub links. This agglomeration of flows leads to reduced travel costs across the interhub links. Current models of hub location do not adequately model the scale economies of flow that accrue due to the agglomeration of flows. This paper shows that current hub location models, by assuming flow-independent costs, not only miscalculate total network cost, but may also erroneously select optimal hub locations and allocations. The model presented in this paper more explicitly models the scale economies that are generated on the interhub links and in doing so provides a more reliable model representation of the reality of hub and spoke networks.     

基于人工神经网络的柴油机故障诊断

故障诊断是计算机模式识别领域的一个活跃课题。文中提出了基于人工神经网络的柴油机故障诊断方法，设计了适合该诊断系统的BP网络结构，并给出了一种基于黄金分割法改进的BP算法，用来自适应调整网络学习速率。仿真结果表明：该算法具有很快的学习速度和较高的学习精度，完全适用于柴油机故障诊断系统。