基于Web的数据管理系统研究

为适应信号动态检测数据管理需要,应用数据库技术、互联网技术,设计开发了基于Web的全路信号动态检测数据管理系统,面向不同的用户,实现了以B／S方式对信号设备台账的数据库管理和各类检测数据的上传、下栽、实时发布、存储、统计、查询等功能。介绍了系统的基本组成、功能、数据库设计和系统可扩展性、开放式体系结构的构建方法。     

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.     

质量比较仪校准的信息化应用

为规范质量比较仪市场,全国质量密度计量技术委员会制定了《JJF1326-2011质量比较仪校准规范》。本文通过调研市场上现有质量比较仪型号,研发数据采集分析软件, 以实现校准过程的数据采集分析的信息化操作。该项目可以减少校准过程中人员的工作量和操作误差,以提高校准结果的准确性和可靠性。该项目适用于现有市场中50余种型号的质量比较仪校准,可推广应用于砝码校准以及其他质量测量的信息化操作。     

VB中ADO数据访问技术的实现

ActiveX数据对象(ActiveXDataObject,简称ADO)是由微软公司推出的以ActiveX技术为基础的一组基于OLBDB数据的高级自动化应用层接口,是一种新型的数据访问方法。它具有速度快、使用方便、内存占用少等特点,目前已成为数据访问技术的一个发展方向。着重介绍了在VB中使用ADO数据访问技术的方法。     

关角隧道进口段浅埋砂层隧道稳定性特征研究

文章运用突变理论,对关角隧道进口段浅埋砂层隧道的稳定性进行研究,揭示不同的应力释放率下围岩的变形规律,并在此基础上确定隧道变形的极限位移,用以指导设计和施工。     

汽车传动系统机械故障诊断方法的研究

本文针对汽车传动系统主要零部件的特点，研究了基于振动信号的故障诊断方法，包括特征提取、模式分类和诊断决策全过程。     

A hybrid Bayesian Network approach to detect driver cognitive distraction

Driver cognitive distraction (e.g., hand-free cell phone conversation) can lead to unapparent, but detrimental, impairment to driving safety. Detecting cognitive distraction represents an important function for driver distraction mitigation systems. We developed a layered algorithm that integrated two data mining methods—Dynamic Bayesian Network (DBN) and supervised clustering—to detect cognitive distraction using eye movement and driving performance measures. In this study, the algorithm was trained and tested with the data collected in a simulator-based study, where drivers drove either with or without an auditory secondary task. We calculated 19 distraction indicators and defined cognitive distraction using the experimental condition (i.e., “distraction” as in the drives with the secondary task, and “no distraction” as in the drives without the secondary task). We compared the layered algorithm with previously developed DBN and Support Vector Machine (SVM) algorithms. The results showed that the layered algorithm achieved comparable prediction performance as the two alternatives. Nonetheless, the layered algorithm shortened training and prediction time compared to the original DBN because supervised clustering improved computational efficiency by reducing the number of inputs for DBNs. Moreover, the supervised clustering of the layered algorithm revealed rich information on the relationship between driver cognitive state and performance. This study demonstrates that the layered algorithm can capitalize on the best attributes of component data mining methods and can identify human cognitive state efficiently. The study also shows the value in considering the supervised clustering method as an approach to feature reduction in data mining applications.     

Estimates of vertical mixing during a Lagrangian experiment off the Galician coast

An adjoint 1-D model was used to determine vertical diffusivity coefficients from temperature profiles collected within a filament escaping from the Galician coast following an upwelling event. The optimisation scheme ended with relatively high diffusivity values within the thermocline (9×10⁻⁵ m² s⁻¹). Such high values are relevant for biogeochemical exchanges between surface and deep waters in stratified areas.The optimised values were several orders of magnitude higher than the bulk of diffusivity measurements recorded with a free-falling device; however, the optimisation solution was consistent with the arithmetic mean of the measurements in the thermocline (7.7×10⁻⁵ m² s⁻¹), giving more weight to the few largest values. Below the thermocline, the data assimilation method failed because of the three-dimensional nature of the advective field of the upwelling system. Ignoring this advective forcing in the model led to estimates that were two orders of magnitude too high.The results suggest that turbulent mixing is a random process where a few intense events determine the average mixing that drives the long-term evolution of the water column structure. This statistical property is very important when one wants to use instantaneous diffusivity measurements for modelling purposes.     

未开放代码整车系统间BOM传递方案研究及应用

整车企业系统之间,因为底层代码不开放,数据结构逻辑未知等困难,无法实现精准对接。致力于通过大数据分析,数据结构排列组合等方法,验证出未开放系统的底层数据逻辑,实现数据关键字段管理。得出工程数据系统关键字段,不仅包含业务信息,还存在内核字段的结论。在无法获知底层封装代码的情况下,找到一条系统间从数据本身研究数据底层逻辑结构的有效论证和系统开发方法,建立精准变更对接管理规则,实现数据快速准确传递。