城轨交通通信传输网方案研究

CBTC是基于通信的列车控制系统,是现在城市轨道交通中对列车控制的主流应用技术。根据目前CBTC系统中通信网建设的需要,对适用于CBTC通信系统的几种传输组网技术进行了分析和比较。     

无线局域网规划与应用

介绍无线局域网的构成,以用户需求、WLAN损耗计算、网络大小以及最小干扰等方面详细分析网络规划,并展望网络应用前景。     

应用GPS RTK进行既有铁路里程丈量的精度分析

应用GPSRTK进行既有铁路里程丈量精度分析和试验数据比较,只要对流动站的对中、整平等环节进行有效的控制,其丈量精度高于常规钢尺丈量精度,满足《既有铁路测量技术规则》（TBJ105—1988）中对距离的精度要求,提高了既有铁路平面测绘的效率,也为当前铁路大提速安全作业提供了更加有利的条件。     

基于运量的国民经济效益网络计算法

通过对现行国民经济效益计算方法的研究,运用交通分配理论论证了现行计算方法中运量分析存在的问题。依据交通分配理论和消费者剩余理论,将交通建设项目吸引区内整个路网作为研究对象,建立了基于运量的国民经济效益网络计算法。实例计算表明该方法的有效性。     

Scale-Free Behavior in Weighted Stock Network

A weighted stock network model of stock market is presented based on the complex network theory. The model is a weighted random network, in which each vertex denotes a stock, and the weight assigned to each edge is the cross-correlation coefficient of returns. Analysis of A shares listed at Shanghai Stock Exchange finds that the influence-strength (IS) follows a power-law distribution with the exponent of 2.58. The empirical analysis results show that there are a few stocks whose price fluctuations can powerfully influence the price dynamics of other stocks in the same market. Further econometric analysis reveals that there are significant differences between the positive IS and the negative IS.     

一种基于网络处理器的高速信息发现系统

高速信息采集是千兆网上实现信息发现的难点,基于IXP2800的高速信息发现系统用网络处理器硬件来实现网络实时数据采集和高速信息发现,可为公安、安全、政府、教育和企业等提供一个对网上传播信息进行信息发现的工具。文章介绍了系统的硬件结构、软件结构和性能指标。     

GPS及其在公路测量中的应用

简要介绍了GPS全球定位系统组成原理,总结了GPS测量的特点以及GPS技术在公路测量中的应用。对GPS实时动态(PTK)定位技术在公路测量中的开发和应用进行了论述。     

构建全省网管通信网络平台

为适应电信管理网络向集中管理、集中维护方向发展的趋势,建立数据通信网为现有各分散的网管系统(如电话交换网管、传输网管、支撑网管等)提供一个统一的数据通信网络平台。各网管系统的信息都可以在此数据通信网上进行传递,使数据通信网成为一个真正的综合数据通信网。其网络结构是采用以省为中心,辐射地、市的广域网络,形成双星形网络结构。     

A Comparative Study of Three Multivariate Short-Term Freeway Traffic Flow Forecasting Methods With Missing Data

Short-term traffic flow forecasting is a critical function in advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS). Accurate forecasting results are useful to indicate future traffic conditions and assist traffic managers in seeking solutions to congestion problems on urban freeways and surface streets. There is new research interest in short-term traffic flow forecasting due to recent developments in intelligent transportation systems (ITS) technologies. Previous research involves technologies in multiple areas, and a significant number of forecasting methods exist in the literature. However, most studies used univariate forecasting methods, and they have limited forecasting abilities when part of the data is missing or erroneous. While the historical average (HA) method is often applied to deal with this issue, the forecasting accuracy cannot be guaranteed. This article makes use of the spatial relationship of traffic flow at nearby locations and builds up two multivariate forecasting approaches: the vector autoregression (VAR) and the general regression neural network (GRNN) based forecasting models. Traffic data collected from U.S. Highway 290 in Houston, TX, were used to test the model performance. Comparison of performances of the three models (HA, VAR, and GRNN) in different missing ratios and forecasting time intervals indicates that the accuracy of the VAR model is more sensitive to the missing ratio, while on average the GRNN model gives more robust and accurate forecasting with missing data, particularly when the missing data ratio is high.     

船舶航向自适应神经网络鲁棒跟踪控制

针对存在不确定性和带有完全未知时变环境扰动的船舶航向非线性控制系统,将指令滤波技术和反步法相结合,设计了一种船舶航向自适应神经网络鲁棒跟踪控制器,该控制器的提出不依赖于外部扰动任何的先验信息。首先,利用神经网络补偿船舶航向非线性控制系统中的非线性项;设计自适应律在线更新神经网络权重向量和估计时变环境扰动的未知界。为了避免传统反步法中对虚拟控制律的反复求导,引入指令滤波技术,使得所设计的航向自适应神经网络跟踪控制器具有结构简单、易于工程实现的特点。理论分析表明,所设计的控制器能使船舶实际输出航向以任意期望的精度跟踪给定的参考航向,保证船舶航向闭环控制系统中所有信号一致最终有界。最后,以大连海事大学远洋实习船“育龙”轮为例进行仿真,仿真结果验证了所提控制器的有效性和鲁棒性。