Modeling time-of-day car use behavior: A Bayesian network approach

In this research, a Bayesian network (BN) approach is proposed to model the car use behavior of drivers by time of day and to analyze its relationship with driver and car characteristics. The proposed BN model can be categorized as a tree-augmented naive (TAN) Bayesian network. A latent class variable is included in this model to describe the unobserved heterogeneity of drivers. Both the structure and the parameters are learned from the dataset, which is extracted from GPS data collected in Toyota City, Japan. Based on inferences and evidence sensitivity analysis using the estimated TAN model, the effects of each single observed characteristic on car use measures are tested and found to be significant. The features of each category of the latent class are also analyzed. By testing the effect of each car use measure on every other measure, it is found that the correlations between car use measures are significant and should be considered in modeling car use behavior.     

802.1x协议在铁路无线局域网中的应用

介绍无线局域网存在的主要安全问题和当今比较主流的无线局域网安全解决技术,其中阐述了最新的802.1x协议,解释其基本原理及该协议在铁路无线局域网中的应用.     

Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach

Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization.     

勘测设计一体化中工经专业数据接口方案探讨

通过勘测设计一体化工经专业基础数据及接口方案的研究，对工经专业基础数据结构设计及专业间接口提出了3个方案并进行分析探讨。     

ARIMA模型在HIS预测中的初步研究

时间序列预测分析在医院信息系统中具有广泛的应用前景,而ARIMA模型是挖掘时间序列模式的一个有效的方法.介绍利用ARIMA模型发现时间序列模式的方法,并应用于医院时序数据预测,为管理层提供决策依据,完善医院信息系统.     

基于TCP/IP拥塞控制的算法研究

在WPAN上使用TCP的关键在于拥塞控制，根据TCP的拥塞控制机制，通过分析拥塞控制的闭环控制原理、TCP／IP拥塞控制所使用的典型技术，研究TCP／IP拥塞控制在无线网上应用的算法。     

提高固定资产投资价格统计数据质量的探讨

文章针对目前建筑安装工程固定资产价格统计工作的现状,分析影响施工企业固定资产投资价格统计数据质量的主要因素,从把握工作重点的原则和解决工作难点等四个方面,提出了提高施工企业固定资产投资价格统计数据质量的对策。     

基于空间数据模型的产业集聚发展分析

产业集聚战略已成为我国各级地方政府发展经济的一项重要政策措施.以空间统计为主要研究方法,应用格点数据模型,对地方产业集聚现象进行研究分析,可以有效了解当地经济发展状况,合理规划地区经济发展方向.     

SETBOC协议分析及其再改进方案

基于单向身份认证技术的安全电子交易协议SETBOC(Secure E lectron ic Transation Based onOne-way Certification)具有效率高,易实现的优点,分析了SETBOC改进方案的优点和不足。在保留原协议及其改进协议优点的基础上,提出再改进方案,使SETBOC协议满足非数字商品交易的原子性。再改进后的协议保证了商家与顾客的交易更加公平。     

数据挖掘技术及在铁道牵引供电系统中的应用

本文概述了数据挖掘的基本原理和方法,及其在铁道牵引供电系统中的作用,提出了挖掘过程中应采用的相关步骤和方法。数据挖掘技术对科学地安排行车调度、电力系统的负荷预测、设备故障诊断具有重要的指导意义。